From c8d895330b24f46c71bf468485c9d22f1d6b1e60 Mon Sep 17 00:00:00 2001
From: pbuabthong <pbuabthong@gmail.com>
Date: Thu, 8 Aug 2024 17:51:27 +0000
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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PointPillars ([https://arxiv.org/abs/1812.05784](https://arxiv.org/abs/1812.05784))\n- เวลานับ 100 ชั่วโมงกับการเขียนแต่งเติมโมเดล รวมไปถึงการเปลี่ยน architecture และปรับแต่ง loss function ขึ้นมาเอง\n- ประสิทธิภาพของโมเดลดีกว่า PointPillars อดีตโมเดลที่ดีที่สุดโมเดลหนึ่ง ใน validation set เดียวกัน\n- เป้าหมายคือการพัฒนาให้ดีพอจะตีพิมพ์ใน conference ระดับโลกได้ในชื่อ PatrickNet\n- รางวัลขวัญใจกรรมการในแง่ความเป็นเลิศทางเทคนิค ได้ใจกรรมการไปอย่างท่วมท้นจากการค้นคว้างานวิจัยหลากหลายงานจากงานวิชาการทั้งเก่าและใหม่ด้วยตนเอง\n- ดูผลการทำนายได้ทาง webapp ที่ถูก deploy บน Heroku\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e \"อยากนำความรู้ความสามารถที่ได้รับจากการเข้าร่วมโครงการ มาพัฒนาโปรเจคของตนเองเพื่อสร้างปัญญาประดิษฐ์ที่มีประโยชน์ต่อสังคมและประเทศชาติ\"\n\u003e\n\u003e \"[https://github.com/PatrickChoDev/SignerCSLR](https://github.com/PatrickChoDev/SignerCSLR) เป็นผลงานที่ผมภาคภูมิใจในการนำเสนอเกี่ยวกับปัญญาประดิษฐ์เพราะเป็นหนึ่งในผลงานของผมที่ได้สร้างเครื่องมือแปลภาษามือด้วยเทคนิค Transformer และ CNN+BiRNN เพื่อใช้สื่อสารกับผู้พิการ แต่ประสิทธิภาพยังไม่ค่อยดีมากเท่าไหร่ จึงอยากที่จะพัฒนาต่อแต่ความรู้ที่ได้จากการคว้าไม่พอครับ แรงบันดาลใจในการพัฒนาปัญญาประดิษฐ์ส่วนใหญ่จะมาจาก JARVIS ที่เป็นผู้ช่วยเสทอนของไอรอนแมน ซึ่งถ้านำมาใช้งานได้จริง น่าจะมีประโยชน์หลายๆด้านเลยครับ\"\n\u003e\n\u003eหลังจบการศึกษา:\n\u003e\n\u003e\"ตั้งใจทำเรื่องนี้เพราะคิดว่า Deep learning ควรจะเข้ามาเป็นส่วนหนึ่งในชีวิตประจำวันของเรา เพราะว่าอีกไม่นานโลกก็จะก้าวเข้าสู่ยุค 5.0 ที่จะเน้นเรื่องความสัมพันธ์ระหว่างมนุษย์กับ Machine แตกต่างจากมุมมองยุค 4.0 ว่า AI จะเข้ามาแย่งงานพวกเรากันหมด ซึ่งเป็นความคิดที่ผิดมหันต์หลังจากได้มาทำความรู้จักกับ AI อย่างถ่องแท้จากพี่ๆ mentors ใน AI Builders และผมมองว่าประเทศไทยก็ควรจะมีเทคโนโลยีเป็นของตัวเอง เพื่อให้คนภายในประเทศได้ภาคูมิใจว่าได้ใช้ของๆคนไทยกันเอง เลยเห็นว่า Autonomous Vehicle เป็นกระแสที่มาแรงและเข้ากับ Idea 5.0 เลยตั้งใจทำโปรเจคนี้ขึ้นมา ถึงแม้จะเป็นส่วนเล็กๆของ Autonomous Vehicle แต่ก็จะน่าจะช่วยทำให้ระบบ AV ทำงานได้ดีขึ้นด้วยการ Improve และ optimize ให้ใช้ได้ในชีวิตจริงๆ ไม่จำเป็นต้องถูกเป๊ะแบบบางงานวิจัยที่เน้นประสิทธิภาพแต่ไม่ได้เน้นเรื่องของเวลารันไทม์ครับ\"\n\u003e\n\u003e \"สำหรับ PatrickNet จะเป็นโมเดลที่ถูกพัฒนาต่อจากงานที่ผมทำในค่าย AI Builders และจะออกมาในรูปแบบของงานวิจัยเพือให้ผู้คนที่สนใจได้ศึกษาต่อ โดยคร่าวๆผมจะใช้เทคนิคที่ดีขึ้น ไวขึ้น เพื่อให้คงประสิทธภาพเดิมได้ แต่ใช้เวลาในการประมวลผลที่น้อยที่สุด และจะมีการนำ Image เข้ามาใช้ด้วยเพื่อเพิ่มประสิทธิภาพใน Real world application จากเหตุการณ์ที่ไม่คาดคิดที่ LiDAR มองไม่เห็นครับ\"\n\u003e\n\u003e\"ฝากถึงน้องๆ AI Builders รุ่นถัดไปว่า ถึงแม้ว่าเราจะเป็นคนๆหนึ่งที่อาศัยอยู่บนโลกใบนี้ มันน่าจะดีถ้าเราได้ทำอะไรไว้ให้กับคนรุ่นต่อๆไป ดีกว่าที่เราจะปล่อยให้เวลาแต่ละวันของเราผ่านไปอย่างไม่มีจุดหมาย ถึงแม้จะยากแค่ไหนแต่เพียงแค่ใจเรามีคำว่า 'สู้' เราก็ไปต่อได้ครับ AI Builders เป็นค่ายดีๆที่ควรเข้าเพราะพี่ๆ Mentors 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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PointPillars ([https://arxiv.org/abs/1812.05784](https://arxiv.org/abs/1812.05784))\n- เวลานับ 100 ชั่วโมงกับการเขียนแต่งเติมโมเดล รวมไปถึงการเปลี่ยน architecture และปรับแต่ง loss function ขึ้นมาเอง\n- ประสิทธิภาพของโมเดลดีกว่า PointPillars อดีตโมเดลที่ดีที่สุดโมเดลหนึ่ง ใน validation set เดียวกัน\n- เป้าหมายคือการพัฒนาให้ดีพอจะตีพิมพ์ใน conference ระดับโลกได้ในชื่อ PatrickNet\n- รางวัลขวัญใจกรรมการในแง่ความเป็นเลิศทางเทคนิค ได้ใจกรรมการไปอย่างท่วมท้นจากการค้นคว้างานวิจัยหลากหลายงานจากงานวิชาการทั้งเก่าและใหม่ด้วยตนเอง\n- ดูผลการทำนายได้ทาง webapp ที่ถูก deploy บน Heroku\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e \"อยากนำความรู้ความสามารถที่ได้รับจากการเข้าร่วมโครงการ มาพัฒนาโปรเจคของตนเองเพื่อสร้างปัญญาประดิษฐ์ที่มีประโยชน์ต่อสังคมและประเทศชาติ\"\n\u003e\n\u003e \"[https://github.com/PatrickChoDev/SignerCSLR](https://github.com/PatrickChoDev/SignerCSLR) 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เลยตั้งใจทำโปรเจคนี้ขึ้นมา ถึงแม้จะเป็นส่วนเล็กๆของ Autonomous Vehicle แต่ก็จะน่าจะช่วยทำให้ระบบ AV ทำงานได้ดีขึ้นด้วยการ Improve และ optimize ให้ใช้ได้ในชีวิตจริงๆ ไม่จำเป็นต้องถูกเป๊ะแบบบางงานวิจัยที่เน้นประสิทธิภาพแต่ไม่ได้เน้นเรื่องของเวลารันไทม์ครับ\"\n\u003e\n\u003e \"สำหรับ PatrickNet จะเป็นโมเดลที่ถูกพัฒนาต่อจากงานที่ผมทำในค่าย AI Builders และจะออกมาในรูปแบบของงานวิจัยเพือให้ผู้คนที่สนใจได้ศึกษาต่อ โดยคร่าวๆผมจะใช้เทคนิคที่ดีขึ้น ไวขึ้น เพื่อให้คงประสิทธภาพเดิมได้ แต่ใช้เวลาในการประมวลผลที่น้อยที่สุด และจะมีการนำ Image เข้ามาใช้ด้วยเพื่อเพิ่มประสิทธิภาพใน Real world application จากเหตุการณ์ที่ไม่คาดคิดที่ LiDAR มองไม่เห็นครับ\"\n\u003e\n\u003e\"ฝากถึงน้องๆ AI Builders รุ่นถัดไปว่า ถึงแม้ว่าเราจะเป็นคนๆหนึ่งที่อาศัยอยู่บนโลกใบนี้ มันน่าจะดีถ้าเราได้ทำอะไรไว้ให้กับคนรุ่นต่อๆไป ดีกว่าที่เราจะปล่อยให้เวลาแต่ละวันของเราผ่านไปอย่างไม่มีจุดหมาย ถึงแม้จะยากแค่ไหนแต่เพียงแค่ใจเรามีคำว่า 'สู้' เราก็ไปต่อได้ครับ AI Builders เป็นค่ายดีๆที่ควรเข้าเพราะพี่ๆ Mentors เก่งและใจดีทุกท่านเลยครับ\"\n","date":"2021-07-05","title":"LiDAR 3D Point Cloud Object Detection for Autonomous Vehicle","builder":"Thanapat Chotipun (Patrick)","builder_info":"มัธยมศึกษาปีที่ 5 / กรุงเทพมหานคร","thumbnail":"/images/2021/002/01.png","links":{"github":"https://github.com/PatrickChoDev/LiDAR-ObjDetect","facebook":"https://www.facebook.com/aibuildersx/posts/166119965556451","blog":"https://patrickchodev.medium.com/patrickchodev-3d-object-detection-using-point-clouds-4106f26dd0d2"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2021","id":"002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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ความท้าทายคือข้อมูลคู่ประโยคไทย-จีนที่เป็นชุดข้อมูลเปิดมีน้อยมาก (\u003c1 ล้านคู่ประโยค) เมื่อเทียบกับภาษาอังกฤษ (\u003e4 ล้านคู่ประโยค)\n- เทรนด้วยสถาปัตยกรรม 6-layer transformer ตามแบบ MarianMT\n- สร้างกฎการทำความสะอาดข้อมูลเองทั้งหมดด้วย 1. ความคล้ายกันของประโยคโดยใช้ multilingual universal sentence encoder 2. อัตราส่วนจำนวนคำ/ตัวอักษรของทั้งสองภาษาในคู่ประโยคเดียวกัน 3. ทำความสะอาดคู่ประโยคที่ไม่ใช่ภาษาที่ต้องการ เช่น ประโยคที่ควรเป็นภาษาจีนแต่ข้อมูลเป็นภาษาอังกฤษ\n- ใช้ความรู้ภาษาจีนระดับสูงให้เป็นประโยชน์ในการคัดเลือกว่า threshold ใดจะตัดคู่ประโยคไหนออก-จะเก็บคู่ประโยคไหนไว้\n- สร้างตัวตัดคำย่อด้วย sentencepiece (unigram model) เพื่อตัดคำทั้งไทยและจีนพร้อมกัน (shared vocabulary)\n- ข้อมูลเทรนจาก OPUS และข้อมูลที่แปลอังกฤษเป็นจีน (backtranslation) ของ scb-mt-en-th-2020 (เดิมเป็นไทย-อังกฤษ) รวม 5 ล้านประโยค (หลังทำความสะอาดแล้ว)\n- เลือกโมเดลที่ดีที่สุดจาก validation set 5 หมื่นประโยค\n- ทดสอบผลบนข้อมูล TED2021 v1 จำนวน 1,226 คู่ประโยค; ไม่ใช้ข้อมูลจาก TED2021 v1 ในการเทรนโมเดลเลยเพื่อให้ยุติธรรมกับโมเดลอื่นๆที่นำมาเปรียบเทียบ\n- วัดผลโดย BLEU score ได้คะแนน 60-70% ของ Google Cloud Translate API [https://cloud.google.com/translate/](https://cloud.google.com/translate/) และคะแนนสูงกว่า AIforThai (xiaofan;[https://aiforthai.in.th/aiplatform/#/dashboard](https://aiforthai.in.th/aiplatform/#/dashboard)) ของ NECTEC อย่างน้อย 1 เท่า (zh-\u003eth) และอย่างมาก 10 เท่า (th-\u003ezh)\n- ข้อจำกัดของโมเดลในปัจจุบันคือการแปลคำเฉพาะได้ไม่ดีเท่า Google Translate เช่น \"โรงเรียนสวนกุหลาบ\" lalita-mt จะแปลว่า 玫瑰花园学校 (โรงเรียนสวนกุหลาบ; นามทั่วไป) ในขณะที่ Google Translate แปลว่า 苏安库拉布学校 (โรเงเรียนซูอันคู้ลาปู้; นามเฉพาะ)\n- Test set ที่ใช้บางครั้งไม่ได้แปลได้คุณภาพนัก เนื่องจากมาจาก crowdsourcing\n- ตั้งเป้าชนะ Google Translate ให้ได้ภายในสิ้นปี ด้วยการหาชุดข้อมูลเพิ่มและปรับปรุงโมเดล\n- รางวัลขวัญใจกรรมการจากความเป็นไปได้อย่างมหาศาลในการใช้งานในอนาคตอันใกล้ของโมเดล\n- ใช้โมเดลได้ฟรี (cc-by-sa 4.0) ได้ที่ HuggingFace [https://huggingface.co/lalita](https://huggingface.co/lalita); ในขณะที่ Google Cloud Translate API มีค่าใช้จ่าย $20 ต่อ 5M ตัวอักษร\n- วิธีการเทรนโมเดลสามารถปรับใช้ได้กับทุกคู่ภาษา; เป็นไปได้ที่จะใช้ข้อมูล open datasets ทำโมเดลแปลภาษาไทย-ภาษาอะไรก็ได้ที่มีประสิทธิภาพเท่าเทียมกับโมเดลนี้\n- ทดลองเล่นได้ทั้งจาก webapp บน Heroku (รันบน CPU ของ free-tier) หรือ notebook\n- อย่าลืมติดตามช่อง YouTube ของน้องลูกตาลได้ที่ MakeCode for Kids [https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ](https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ) หรือ FB Page [https://www.facebook.com/makecodeforkid](https://www.facebook.com/makecodeforkid)\n- น้องลูกตาลยังทำ MakeCode for Kids เป็น Facebook Page  [https://www.facebook.com/makecodeforkid](https://www.facebook.com/makecodeforkid) และ Youtube Channel [https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ](https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ) สำหรับน้องๆ ชั้นประถมหรือผู้ปกครองที่สนใจการเขียนโปรแกรมและปัญญาประดิษฐ์ ผู้ที่สนใจสามารถไปติดตามกันได้ น้องลูกตาลฝากมาบอกว่ามีคำถามอะไรก็ถามได้เลยครับ\n\n![Project Results](/images/2021/003/02.jpg)\n\n\n![Results Comparison](/images/2021/003/03.jpg)\n\n\n![Hugging Face Deployment](/images/2021/003/04.jpg)\n\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e\"หนูมีความสนใจโครงการนี้ เนื่องจากหนูกำลังศึกษาหาความรู้ทางด้านนี้อยู่ก่อนหน้านี้ ตั้งแต่ประถม ก็เริ่มฝึกเรียนโปรแกรม เริ่มจากภาษา C และได้มีโอกาสไปแข่งขันหุ่นยนต์ ตามรายการต่างๆ  ทั้งในประเทศและต่างประเทศ [https://www.facebook.com/lalitaportfolio](https://www.facebook.com/lalitaportfolio) จนเข้าศึกษามัธยมปีที่ 2 ก็เริ่มสนใจทางด้าน AI และได้เริ่มต้นศึกษา ภาษา Python และหาความรู้ทางด้านนี้ ความตั้งใจส่วนหนึ่ง คือ อยากให้ น้องๆ ตั้งแต่ระดับประถม สามารถเข้าถึง ความรู้ทางด้าน robot และ AI ให้ได้มากขึ้น ผ่านการเรียนรู้ในรูปแบบง่ายๆ เลยได้ทำ page facebook ที่เกี่ยวกับการ coding และ AI page MakeCode for Kids [https://www.facebook.com/makecodeforkid](https://www.facebook.com/makecodeforkid)\"\n\u003e\"หนูได้มีการเริ่มต้นใช้โปรแกรม AI Machine Learning แบบสำเร็จรูปมาใช้ซึ่งทำให้หนูอยากที่จะเรียนรู้การทำงานแบบที่ใช้งานกันจริงๆ ในอนาคตเพื่อให้เข้าใจ-มีความรู้ทางด้านนี้ และมีแนวทางในการศึกษาต่อทางด้านนี้\"","date":"2021-07-06","title":"Lalita Chinese-Thai Machine Translation ","builder":"Lalita Deelert (Looktarn)","builder_info":"มัธยมศึกษาปีที่ 3 / กรุงเทพมหานคร","thumbnail":"/images/2021/003/01.jpg","links":{"github":" https://github.com/LalitaDeelert/lalita-mt-zhth","facebook":"https://www.facebook.com/aibuildersx/posts/166736255494822","blog":"https://bit.ly/3hhVZWL"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2021","id":"003-Lalita-Chinese-Thai-Machine-Translation"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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ความท้าทายคือข้อมูลคู่ประโยคไทย-จีนที่เป็นชุดข้อมูลเปิดมีน้อยมาก (\u003c1 ล้านคู่ประโยค) เมื่อเทียบกับภาษาอังกฤษ (\u003e4 ล้านคู่ประโยค)\n- เทรนด้วยสถาปัตยกรรม 6-layer transformer ตามแบบ MarianMT\n- สร้างกฎการทำความสะอาดข้อมูลเองทั้งหมดด้วย 1. ความคล้ายกันของประโยคโดยใช้ multilingual universal sentence encoder 2. อัตราส่วนจำนวนคำ/ตัวอักษรของทั้งสองภาษาในคู่ประโยคเดียวกัน 3. ทำความสะอาดคู่ประโยคที่ไม่ใช่ภาษาที่ต้องการ เช่น ประโยคที่ควรเป็นภาษาจีนแต่ข้อมูลเป็นภาษาอังกฤษ\n- ใช้ความรู้ภาษาจีนระดับสูงให้เป็นประโยชน์ในการคัดเลือกว่า threshold ใดจะตัดคู่ประโยคไหนออก-จะเก็บคู่ประโยคไหนไว้\n- สร้างตัวตัดคำย่อด้วย sentencepiece (unigram model) เพื่อตัดคำทั้งไทยและจีนพร้อมกัน (shared vocabulary)\n- ข้อมูลเทรนจาก OPUS และข้อมูลที่แปลอังกฤษเป็นจีน (backtranslation) ของ scb-mt-en-th-2020 (เดิมเป็นไทย-อังกฤษ) รวม 5 ล้านประโยค (หลังทำความสะอาดแล้ว)\n- เลือกโมเดลที่ดีที่สุดจาก validation set 5 หมื่นประโยค\n- ทดสอบผลบนข้อมูล TED2021 v1 จำนวน 1,226 คู่ประโยค; ไม่ใช้ข้อมูลจาก TED2021 v1 ในการเทรนโมเดลเลยเพื่อให้ยุติธรรมกับโมเดลอื่นๆที่นำมาเปรียบเทียบ\n- วัดผลโดย BLEU score ได้คะแนน 60-70% ของ Google Cloud Translate API [https://cloud.google.com/translate/](https://cloud.google.com/translate/) และคะแนนสูงกว่า AIforThai (xiaofan;[https://aiforthai.in.th/aiplatform/#/dashboard](https://aiforthai.in.th/aiplatform/#/dashboard)) ของ NECTEC อย่างน้อย 1 เท่า (zh-\u003eth) และอย่างมาก 10 เท่า (th-\u003ezh)\n- ข้อจำกัดของโมเดลในปัจจุบันคือการแปลคำเฉพาะได้ไม่ดีเท่า Google Translate เช่น \"โรงเรียนสวนกุหลาบ\" lalita-mt จะแปลว่า 玫瑰花园学校 (โรงเรียนสวนกุหลาบ; นามทั่วไป) ในขณะที่ Google Translate แปลว่า 苏安库拉布学校 (โรเงเรียนซูอันคู้ลาปู้; นามเฉพาะ)\n- Test set ที่ใช้บางครั้งไม่ได้แปลได้คุณภาพนัก เนื่องจากมาจาก crowdsourcing\n- ตั้งเป้าชนะ Google Translate ให้ได้ภายในสิ้นปี ด้วยการหาชุดข้อมูลเพิ่มและปรับปรุงโมเดล\n- รางวัลขวัญใจกรรมการจากความเป็นไปได้อย่างมหาศาลในการใช้งานในอนาคตอันใกล้ของโมเดล\n- ใช้โมเดลได้ฟรี (cc-by-sa 4.0) ได้ที่ HuggingFace [https://huggingface.co/lalita](https://huggingface.co/lalita); ในขณะที่ Google Cloud Translate API มีค่าใช้จ่าย $20 ต่อ 5M ตัวอักษร\n- วิธีการเทรนโมเดลสามารถปรับใช้ได้กับทุกคู่ภาษา; เป็นไปได้ที่จะใช้ข้อมูล open datasets ทำโมเดลแปลภาษาไทย-ภาษาอะไรก็ได้ที่มีประสิทธิภาพเท่าเทียมกับโมเดลนี้\n- ทดลองเล่นได้ทั้งจาก webapp บน Heroku (รันบน CPU ของ free-tier) หรือ notebook\n- อย่าลืมติดตามช่อง YouTube ของน้องลูกตาลได้ที่ MakeCode for Kids [https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ](https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ) หรือ FB Page [https://www.facebook.com/makecodeforkid](https://www.facebook.com/makecodeforkid)\n- น้องลูกตาลยังทำ MakeCode for Kids เป็น Facebook Page  [https://www.facebook.com/makecodeforkid](https://www.facebook.com/makecodeforkid) และ Youtube Channel [https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ](https://www.youtube.com/channel/UC_N5_4YR3tPwoPMoQ2BTndQ) สำหรับน้องๆ ชั้นประถมหรือผู้ปกครองที่สนใจการเขียนโปรแกรมและปัญญาประดิษฐ์ 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[https://www.facebook.com/makecodeforkid](https://www.facebook.com/makecodeforkid)\"\n\u003e\"หนูได้มีการเริ่มต้นใช้โปรแกรม AI Machine Learning แบบสำเร็จรูปมาใช้ซึ่งทำให้หนูอยากที่จะเรียนรู้การทำงานแบบที่ใช้งานกันจริงๆ ในอนาคตเพื่อให้เข้าใจ-มีความรู้ทางด้านนี้ และมีแนวทางในการศึกษาต่อทางด้านนี้\"","date":"2021-07-06","title":"Lalita Chinese-Thai Machine Translation ","builder":"Lalita Deelert (Looktarn)","builder_info":"มัธยมศึกษาปีที่ 3 / กรุงเทพมหานคร","thumbnail":"/images/2021/003/01.jpg","links":{"github":" https://github.com/LalitaDeelert/lalita-mt-zhth","facebook":"https://www.facebook.com/aibuildersx/posts/166736255494822","blog":"https://bit.ly/3hhVZWL"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2021","id":"003-Lalita-Chinese-Thai-Machine-Translation"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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(ระยะเวลาที่ใช้วาด, จำนวนไลค์ของรูป, จำนวนรูปที่ศิลปินเจ้าของภาพเคยวาด, คะแนนรีวิว, ขนาด-สไตล์ของรูปภาพ) รวม 8,239 ชุด มีราคา 6-120 USD\n- ความพยายามแรกคือทำ image classification ด้วยช่วงราคาช่วงละ 5 USD เพื่อเหมาะกับการใช้งานจริง ไม่ประสบผลสำเร็จเนื่องจากช่วงราคาแคบไปเมื่อเทียบกับการกระจายตัวของราคาที่เป็น power law distribution (รูปราคาถูกๆเยอะ ในขณะที่รูปราคาแพงมีไม่กี่รูป)\n- เปลี่ยนการจัดกลุ่มเป็นการทำด้วย k-means clustering บนตัวแปรราคาตัวแปรเดียว ได้ผลดีขึ้นเล็กน้อย แต่เนื่องจากช่วงราคากว้างมากจึงใช้งานจริงไม่ได้\n- ค้นพบว่าหลายรูปตั้งราคาไม่สมจริง เช่น บางรูปไม่ลงสีแต่ตั้งราคาถึง 21-25 USD (โมเดลทำนายว่า 5-10 USD) จึงตั้งสมมุติฐานว่าศิลปินบางท่านอาจจะตั้งราคาไม่ค่อยเป็น จึงทำการกรองเอาเฉพาะรูปของศิลปินที่เคยส่งงานมาแล้วอย่างน้อย 5 งานเท่านั้น\n- กรองรูปที่ตั้งราคาเว่อร์ไป (outliers) ออกด้วย interquartile range ของ boxplot ทำให้เหลือรูป 2,028 ชุด ราคาระหว่าง 5-90 USD แบ่งเป็น train-validaiton-test set ที่ 80/10/10\n- สร้างโมเดล image regression 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และสังคมโดยรวมอย่างมีจิตสาธารณะ\n\n![Data Augmentation](/images/2021/004/02.png)\n\n\n![Visualization](/images/2021/004/03.png)\n\n\n![Model Deployment](/images/2021/004/04.png)\n\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e\"อยากศึกษาเรื่องการสร้างเอไอมานานแล้วเพราะเห็นว่าต่อยอดได้หลายทางค่ะ (อยากต่อยอดด้านการพัฒนาเกมและความปลอดภัยเครือข่ายเป็นพิเศษ) โดยส่วนตัวสนใจด้านการเขียนโปรแกรมมาตั้งแต่ ม.ต้น จึงเริ่มศึกษาจากการอ่านหนังสือในช่วงปิดเทอม จนได้มีโอกาสเขียนจริงตอน ม.4 ก่อนจะลาออกจากโรงเรียนมาเรียนโฮมสคูลตอน ม.5 เพราะรู้สึกว่าระบบการศึกษาไม่ตอบโจทย์ หลังจากนั้นก็ศึกษาจากคอร์สออนไลน์บ้างแต่ว่าเรื่องเกี่ยวกับการจัดการข้อมูลเป็นเรื่องที่ไม่ถนัดถ้าเทียบกับเรื่องอื่น เคยศึกษาเองจากหนังสือ data science แล้วแต่ไม่ค่อยเข้าใจเท่าไหร่ก็เลยอยากจะหาคอร์สเรียนเลยสนใจลงสมัครโครงการนี้ค่ะ (แบบทดสอบที่ทำก็ต้องเปิดหนังสือกับกูเกิลค่ะเพราะไม่ถนัดแต่อยากพยายามดูTT) และก็ต้องการมีเพื่อนมีสังคมคนชอบไอทีด้วยเพราะเพื่อนที่ รร. อยากทำงานด้วยการแพทย์หรือสถาปัตย์กันเกือบทุกคน\"\n\u003eหลังจบการศึกษา:\n\u003e\n\u003e\"อนาคตก็อยากจะพัฒนาต่อให้โมเดลมีประสิทธิภาพดีกว่านี้ค่ะ อยากเป็นกำลังใจให้ทุกคนที่วาดรูปคอมมิชชัน อยากให้ทุกคนเห็นคุณค่าในงานของตัวเองมาก ๆ ทุกคนเก่งมากนะเราเชื่อแบบนั้น แล้วก็ขอขอบคุณโครงการมากเลยค่ะจากที่ตอนแรกเราไม่มีความรู้ด้าน machine learning เลยแต่ก็ทำมาได้ขนาดนี้เป็นเพราะได้เทคนิคและคำแนะนำดี ๆ จากพี่ ๆ เมนเทอร์ทุกคน อยากเชิญชวนเพื่อน ๆ วัยมัธยมที่สนใจด้าน machine learning มาสมัครโครงการนี้ในรุ่นถัดไปกันค่ะ เราจะได้มีโมเดลใหม่ ๆ มาช่วยแก้ปัญหาส่วนตัวและปัญหาสังคมกันเนอะ😉\"","date":"2021-07-07","title":"แนะนำราคารูปคอมมิชชันอนิเมะด้วย machine learning โดย fastai","builder":"Prad Rattanakijsoonthorn (BB)","builder_info":"มัธยมศึกษาปีที่ 5 / 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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มีการทำการทดลองถึงความแตกต่างระหว่างการใช้ full stop และ ไม่มี full stop\n- ได้เทรน model ไปจำนวนทั้งหมด 10,000 steps\n- วัดผลด้วย mean opinion score ได้คะแนน 3.13 +- 1.12 โดยเสียงมนุษย์ได้อยู่ที่ 4.3\n\n![Model Architecture](/images/2021/005/02.png)\n\n\n![Experiment Steps](/images/2021/005/03.png)\n\n\n![Results](/images/2021/005/04.png)\n\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e\"“AI Builder is the fascinating program to encourage and create youth \"AI builders\". \n\u003eAI, the Artificial Intelligence, is definitely the trendy, most practical tools for us to live our life. With this significance, AI should be the best topic to learn in order to improve our daily basis and transferring into a \"Tech\" era. These technologies are improving every day, we shouldn't be behind the times.\n\u003eI would love to join AI Builder program to develop our country, together, and improving our lives' quality with AI.”","date":"2021-07-08","title":"Thai Text-to-Speech with Tacotron","builder":"Rajasurang Wongkrasaemongkol (Prim)","builder_info":"มัธยมศึกษาปีที่ 2 / ภูเก็ต","thumbnail":"/images/2021/005/01.png","links":{"github":" https://github.com/Prim9000/Thai_TTS","facebook":"https://www.facebook.com/aibuildersx/posts/168189225349525","blog":"https://bit.ly/3jHNuWu"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2021","id":"005-Thai-Text-to-Speech-with-Tacotron"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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diff --git "a/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.html" "b/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.html"
index 0dd77a1..c574670 100644
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+++ "b/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.html"
@@ -1 +1 @@
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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spectrogram ขึ้นมาจาก latent space\n- ทำการวัดผลโมเดลตัวเองด้วย Mean Opinion Score (MOS) ได้ผลลัพท์ดีที่สุดอยู่ที่ 3.56 (เต็ม 5)\n- สามารถเล่น demo app ได้ทีทาง [heroku app](https://rew-thai-music-generation.herokuapp.com/)\n\n![Generation example](/images/2021/007/01.jpg)\n\n![Model Architecture](/images/2021/007/02.jpg)\n\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e “นับเป็นโอกาสที่ดีที่จะได้เข้าร่วมในโครงการ AI Builder เพื่อศึกษาต่อยอดความรู้ทางด้าน Machine Learning เนื่องจากว่า Artificial Intelligence กำลังมีบทบาทสำคัญในหลายสาขาวิชา และมีประโยชน์ในการพัฒนาเทคโนโลยีเพื่อแก้ไขปัญหาในทุกๆระดับ ตั้งแต่ระดับบุคคล ไปจนถึงระดับชาติ ดังนั้นผมจึงอยากเข้าเป็นส่วนหนึ่งของโครงการนี้เพื่อ\n\u003e1. เปิดวิสัยทัศน์จากการได้เรียนรู้จากอาจารย์และพี่ๆในโครงการที่มีความรู้ด้านการพัฒนาปัญญาประดิษฐ์โดยตรง รวมทั้งได้คำปรึกษาที่มีประโยชน์อย่างมากในการพัฒนาต่อยอดองค์ความรู้\n\u003e2. ได้มีส่วนร่วมในการทำโครงการที่เกี่ยวข้องกับปัญญาประดิษฐ์ ซึ่งเป็นการเรียนรู้แบบ 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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spectrogram ขึ้นมาจาก latent space\n- ทำการวัดผลโมเดลตัวเองด้วย Mean Opinion Score (MOS) ได้ผลลัพท์ดีที่สุดอยู่ที่ 3.56 (เต็ม 5)\n- สามารถเล่น demo app ได้ทีทาง [heroku app](https://rew-thai-music-generation.herokuapp.com/)\n\n![Generation example](/images/2021/007/01.jpg)\n\n![Model Architecture](/images/2021/007/02.jpg)\n\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e “นับเป็นโอกาสที่ดีที่จะได้เข้าร่วมในโครงการ AI Builder เพื่อศึกษาต่อยอดความรู้ทางด้าน Machine Learning เนื่องจากว่า Artificial Intelligence กำลังมีบทบาทสำคัญในหลายสาขาวิชา และมีประโยชน์ในการพัฒนาเทคโนโลยีเพื่อแก้ไขปัญหาในทุกๆระดับ ตั้งแต่ระดับบุคคล ไปจนถึงระดับชาติ ดังนั้นผมจึงอยากเข้าเป็นส่วนหนึ่งของโครงการนี้เพื่อ\n\u003e1. เปิดวิสัยทัศน์จากการได้เรียนรู้จากอาจารย์และพี่ๆในโครงการที่มีความรู้ด้านการพัฒนาปัญญาประดิษฐ์โดยตรง รวมทั้งได้คำปรึกษาที่มีประโยชน์อย่างมากในการพัฒนาต่อยอดองค์ความรู้\n\u003e2. ได้มีส่วนร่วมในการทำโครงการที่เกี่ยวข้องกับปัญญาประดิษฐ์ ซึ่งเป็นการเรียนรู้แบบ learning by doing ซึ่งเป็นการเรียนรู้จากประสบการณ์จริง ได้ผลงานที่สามารถจำต้องได้\n\u003e3. ได้เป็นส่วนเล็กๆส่วนหนึ่งที่สำคัญของ AI community ในฐานะยุวทูตด้านดิจิทัล ได้มีส่วนร่วมในการแบ่งปันความรู้ และทำให้เกิด community ที่แข็งแรง\n\u003eสุดท้ายนี้ผมคาดหวังที่จะสามารถเป็นผู้นำในการพัฒนานวัตกรรมด้านปัญญาประดิษฐ์ที่เป็นประโยชน์ต่อสังคมและประเทศชาติต่อไปในอนาคต”\n","date":"2021-07-10","title":"Thai Music (Ranat Ek) Generation with Variational Autoencoder","builder":"Noppawat Tantisiriwat (Rew)","builder_info":"มัธยมศึกษาปีที่ 6 / 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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วิธีการเตรียมชุดข้อมูลคือ การนำข้อมูลที่ถูกเก็บมาแบ่งเป็นช่วงเวลาสั้นๆ (เพื่อเลียนแบบการขยับของนิ้วมือจริงๆ) โดยเตรียมไว้ 2 แบบคือ 1 วินาที และ 0.2 วินาที\n- การเตรียมข้อมูลนั้น เนื่องจากข้อมูลเป็น “สัญญาณ” ไฟฟ้า เลยแปลง “สัญญาณ” จาก time-domain ให้อยู่บน frequency-domain ด้วยวิธี short-time fourier transform\n- เมื่อแปลงให้อยู่บน frequency-domain แล้วก็นำข้อมูลแปลงเป็น spectrogram และนำ ข้อมูลสอง channel มาต่อกัน (concatenate) \n- Model ที่ใช้คือการนำ Resnet-34 มา fine-tune\n- ผลลัพธ์พบว่า model 1 วินาทีมีความแม่นยำที่ 99.2% และ model 0.2 วินาทีมีความแม่นยำ 77.2%\n- ทั้งนี้เมื่อทำการนำ model ไปใช้งานบนข้อมูลที่ถูก simulation ขึ้นเพื่อการจำลองของแขนนั้น พบว่า model 0.2 วินาทีทำงานได้ดีกว่า เนื่องจากการขยับมือของคนเรานั้นไม่ได้ใช้เวลานานถึงขนาด 1 วินาที\n- สิ่งที่จะนำไปต่อยอดคือ การนำไป implement ลงบนแขนเทียมเพื่อช่วยเหลือผู้พิการ\n\n![Preprocessing](/images/2021/009/02.jpg)\n\n\n![Results](/images/2021/009/03.jpg)\n\n\n![Reference](/images/2021/009/04.jpg)\n\n### 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">- Visual Hand - Command things with your hand DIY</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Rapepong Pitijaroonpong (Best)<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5 / ปทุมธานี</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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index 66be616..05d06d3 100644
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+++ "b/2021/016-STONK-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\243\340\270\262\340\270\204\340\270\262\340\270\253\340\270\270\340\271\211\340\270\231\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211-machine-learning.html"
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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1v60ess">.css-1v60ess{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;position:absolute;white-space:nowrap;vertical-align:middle;outline:2px solid 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Hairstyle Recommendation</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Varisa Techapisut (Fye)<!-- --> • <!-- -->มัธยมศึกษาปีที่ 4 / กรุงเทพมหานคร</h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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มีความไม่เป็นระเบียบเรียบร้อย สแกนมาเอียงบ้าง ตัวอักษรซีด เข้มเกิน ทำให้ยากต่อการที่จะอ่านเอกสาร อีกอย่างเมื่อเราดูประกาศ/คำสั่ง/ระเบียบ ของรัฐที่ถูก Publish ขึ้น Website ของหน่วยงานต่างๆ พบว่ามีแค่สกุลไฟล์ .pdf ไม่พบสกุลไฟล์อื่นๆ เช่น text เป็นต้น\n- เลือกทำ OCR กับฟ้อนท์ TH Sarabun เนื่องจากระเบียบการจัดทำ และออกหนังสือประกาศและคำสั่งของทางราชการไทย เพื่อให้เป็นมาตรฐานเดียวกันทั่วประเทศนั้นได้มีการกำหนดการใช้งาน ฟอนต์มาตรฐานแห่งชาติ (National Font) สำหรับการออกหนังสือราชการทุกประเภท คือ ฟอนต์ตระกูล TH Sarabun ขนาด 16–20 px\n- และเมื่อดูในส่วนของ Repository ของ langdata_lstm Tesseract ในส่วนของรายชื่อฟอนต์ที่ใช้ในการ Train tesseract นั้นไม่พบฟอนต์มาตรฐานราชการไทย (ตระกูลฟอนต์ที่ขึ้นต้นด้วย TH) แม้แต่ฟอนต์เดียว\n- ทดลองใช้ทั้ง Tesseract และ easyOCR เลือกใช้ Tessaract เนื่องจากประสิทธิภาพดีกว่าเล็กน้อยสำหรับเอกสารราชการที่นำมาทดสอบ\n- ข้อความสำหรับ train ของ Tesseract เป็นข้อความมั่วๆที่นำมาเรียงต่อกัน ไม่มีความหมาย จึงเปลี่ยนมาใช้ข้อความจากชุดข้อมูลข่าวของ PyThaiNLP และ open source อื่นๆ เช่น prachathai67k, TR-TPBS, ถ้อยคำแถลงการนายกรัฐมนตรี, และรัฐธรรมนูญแห่งราชอาณาจักรไทย \n- เทรนด้วยข้อมูล 50,000 ประโยคและ validate ด้วยข้อมูล 10,000 ประโยค\n- test set เป็นการทดสอบด้วยข้อมูลจริง 110 รูปที่มีขนาดซูม 80-180% มีตัวอักษรซีด/ไม่ชัด ขีดทับตัวอักษร รอยประทับตราทางราชการ ตัวอักษรเอียง\n- วัดผลด้วย character error rate (CER; ยิ่งน้อยยิ่งดี) เฉลี่ยได้ที่ 4.8% (Tesseract แบบไม่ finetune ได้ 5.4%; T-OCR ของ AI for Thai / NECTEC ได้ 13.6%)\n\n![Problem Statement](/images/2021/020/02.jpg)\n\n\n![Tesseract](/images/2021/020/03.jpg)\n\n\n![Deployment](/images/2021/020/04.jpg)\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e \"แรงบันดาลใจที่ผมสมัครเข้าโครงการในครั้งนี้ก็มาจากการที่เห็นพี่ๆ ที่ติดตามและรู้จัก ที่มีความรู้ด้านของ AI ก็ได้เห็นทั้ง Blog ผลงานต่างๆ ก็รู้สึกว่าเห้ยย โคตรเจ๋งเลย สักวันอยากจะเก่งเหมือนพี่เขามั่ง อีกข้อก็จะเป็นในส่วนของอยากจะมีความรู้ ทักษะด้าน AI ไปช่วยครูในการพัฒนาระบบงานต่างๆของโรงเรียน ลดค่าซื้อระบบเอางบไปลงทุนกับส่วนอื่น ละก็อยากที่จะเป็นความรู้ติดตัวไปใช้ในงานหรือการเรียนในอนาคตด้วยครับ ในการเรียน AI อาจจะมีบางเรื่องที่เป็นเรื่องที่ใหม่ และยากสำหรับผมแต่ผมเชื่อในคติที่ผมยึดถือมาตลอดและได้พิสูจน์แล้วว่า ไม่ฝึกก็ไม่มีวันทำได้ ไม่ขวนขวายก็ไม่มีวันสำเร็จครับ\"\n\u003e \"ในปัจจุบันเรื่อง Ai เป็นเรื่องที่มี effect ต่อสังคม วงการเทคโนโลยีของเราอย่างมาก สามารถที่จะ เปลี่ยนแปลงขับเคลื่อนสิ่งต่างๆ อย่างก้าวกระโดดตลอดที่ผมเขียนโปรแกรมมา หลายงานๆ ทั้งส่วนตัว ช่วยรร. มีหลายๆงานที่ต้องการนำ AI เข้ามาช่วยเพื่อปรับปรุงลดขั้นตอนต่างๆ มีหลายครั้งที่ รร. ต้องไปซื้อระบบ AI ราคาหลายหมื่นมาใช้ ซึ่งผมได้มองศึกษาแล้วเป็นเรื่องที่เราสามารถทำได้เอง แต่เรายังขาดความรู้ในการพัฒนา การที่ผมสมัครโครงการนี้เพราะผมเห็นว่าผมจะได้นำความรู้ ประสบการณ์ที่ได้จากโครงการนี้ไปช่วยพัฒนาระบบโรงเรียนผม ถ่ายทอดให้รุ่นน้องดูแลและพัฒนาต่อจากผม เป็นความรู้ที่สามารถใช้เรียนต่อในมหาลัย ไปต่อยอดสู่อาชีพได้\"\n\u003e หลังจบโครงการ:\n\u003e \"หลายๆคนมักจะบอกว่าการทำ OCR เป็นง่ายที่ง่าย ผมเห็นด้วยครับมันง่ายครับ แต่ทำไมกลับไม่มีใครที่คิดลงมือจะทำ? ทั้งๆที่ Tools ของมันครบคันมากๆ หลายๆที่ หลายๆบริษัทก็พยายามชูฟีเจอร์นี้ มันก็เหมือนกับการมีสูตรอาหารที่คุณชอบอยู่ในมือไม่ได้ด้อยกว่าใคร มีวัตถุดิบ ของทุกอย่างครบคัน ขาดแค่คนลงมือทำ แต่ก็ยังไปซื้ออาหารนั้นมาทานอยู่ประจำ ดังนั้นผมขอที่จะเป็นคนพัฒนา OCR เป็นพ่อครัวที่จะทำเมนู OCR Thai เพื่อให้ทุกคนมี Tools OCR Thai ที่ดีไปใช้งาน และเป็นการพัฒนาวงการนี้ให้ใหญ่ขึ้นอีกด้วยครับ\"","date":"2021-07-23","title":"TH National Document OCR (THND OCR) ","builder":"Kampanart Chaimooltan (Cop)","builder_info":"มัธยมศึกษาปีที่ 5 / เชียงใหม่","thumbnail":"/images/2021/020/01.jpg","links":{"github":"https://github.com/copninich/TH-National-Document-OCR/","facebook":"https://www.facebook.com/aibuildersx/posts/","blog":"https://copninich.medium.com/5a673cc8a686"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2021","id":"020-TH-National-Document-OCR-(THNDOCR)"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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มีความไม่เป็นระเบียบเรียบร้อย สแกนมาเอียงบ้าง ตัวอักษรซีด เข้มเกิน ทำให้ยากต่อการที่จะอ่านเอกสาร อีกอย่างเมื่อเราดูประกาศ/คำสั่ง/ระเบียบ ของรัฐที่ถูก Publish ขึ้น Website ของหน่วยงานต่างๆ พบว่ามีแค่สกุลไฟล์ .pdf ไม่พบสกุลไฟล์อื่นๆ เช่น text เป็นต้น\n- เลือกทำ OCR กับฟ้อนท์ TH Sarabun เนื่องจากระเบียบการจัดทำ และออกหนังสือประกาศและคำสั่งของทางราชการไทย เพื่อให้เป็นมาตรฐานเดียวกันทั่วประเทศนั้นได้มีการกำหนดการใช้งาน ฟอนต์มาตรฐานแห่งชาติ (National Font) สำหรับการออกหนังสือราชการทุกประเภท คือ ฟอนต์ตระกูล TH Sarabun ขนาด 16–20 px\n- และเมื่อดูในส่วนของ Repository ของ langdata_lstm Tesseract ในส่วนของรายชื่อฟอนต์ที่ใช้ในการ Train tesseract นั้นไม่พบฟอนต์มาตรฐานราชการไทย (ตระกูลฟอนต์ที่ขึ้นต้นด้วย TH) แม้แต่ฟอนต์เดียว\n- ทดลองใช้ทั้ง Tesseract และ easyOCR เลือกใช้ Tessaract เนื่องจากประสิทธิภาพดีกว่าเล็กน้อยสำหรับเอกสารราชการที่นำมาทดสอบ\n- ข้อความสำหรับ train ของ Tesseract เป็นข้อความมั่วๆที่นำมาเรียงต่อกัน ไม่มีความหมาย จึงเปลี่ยนมาใช้ข้อความจากชุดข้อมูลข่าวของ PyThaiNLP และ open source อื่นๆ เช่น prachathai67k, TR-TPBS, ถ้อยคำแถลงการนายกรัฐมนตรี, และรัฐธรรมนูญแห่งราชอาณาจักรไทย \n- เทรนด้วยข้อมูล 50,000 ประโยคและ validate ด้วยข้อมูล 10,000 ประโยค\n- test set เป็นการทดสอบด้วยข้อมูลจริง 110 รูปที่มีขนาดซูม 80-180% มีตัวอักษรซีด/ไม่ชัด ขีดทับตัวอักษร รอยประทับตราทางราชการ ตัวอักษรเอียง\n- วัดผลด้วย character error rate (CER; ยิ่งน้อยยิ่งดี) เฉลี่ยได้ที่ 4.8% (Tesseract แบบไม่ finetune ได้ 5.4%; T-OCR ของ AI for Thai / NECTEC ได้ 13.6%)\n\n![Problem Statement](/images/2021/020/02.jpg)\n\n\n![Tesseract](/images/2021/020/03.jpg)\n\n\n![Deployment](/images/2021/020/04.jpg)\n\n### แรงจูงใจในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 9 สัปดาห์ที่แล้ว)\n\n\u003e \"แรงบันดาลใจที่ผมสมัครเข้าโครงการในครั้งนี้ก็มาจากการที่เห็นพี่ๆ ที่ติดตามและรู้จัก ที่มีความรู้ด้านของ AI ก็ได้เห็นทั้ง Blog ผลงานต่างๆ ก็รู้สึกว่าเห้ยย โคตรเจ๋งเลย สักวันอยากจะเก่งเหมือนพี่เขามั่ง อีกข้อก็จะเป็นในส่วนของอยากจะมีความรู้ ทักษะด้าน AI ไปช่วยครูในการพัฒนาระบบงานต่างๆของโรงเรียน ลดค่าซื้อระบบเอางบไปลงทุนกับส่วนอื่น ละก็อยากที่จะเป็นความรู้ติดตัวไปใช้ในงานหรือการเรียนในอนาคตด้วยครับ ในการเรียน AI อาจจะมีบางเรื่องที่เป็นเรื่องที่ใหม่ และยากสำหรับผมแต่ผมเชื่อในคติที่ผมยึดถือมาตลอดและได้พิสูจน์แล้วว่า ไม่ฝึกก็ไม่มีวันทำได้ ไม่ขวนขวายก็ไม่มีวันสำเร็จครับ\"\n\u003e \"ในปัจจุบันเรื่อง Ai เป็นเรื่องที่มี effect ต่อสังคม วงการเทคโนโลยีของเราอย่างมาก สามารถที่จะ เปลี่ยนแปลงขับเคลื่อนสิ่งต่างๆ อย่างก้าวกระโดดตลอดที่ผมเขียนโปรแกรมมา หลายงานๆ ทั้งส่วนตัว ช่วยรร. มีหลายๆงานที่ต้องการนำ AI เข้ามาช่วยเพื่อปรับปรุงลดขั้นตอนต่างๆ มีหลายครั้งที่ รร. ต้องไปซื้อระบบ AI ราคาหลายหมื่นมาใช้ ซึ่งผมได้มองศึกษาแล้วเป็นเรื่องที่เราสามารถทำได้เอง แต่เรายังขาดความรู้ในการพัฒนา การที่ผมสมัครโครงการนี้เพราะผมเห็นว่าผมจะได้นำความรู้ ประสบการณ์ที่ได้จากโครงการนี้ไปช่วยพัฒนาระบบโรงเรียนผม ถ่ายทอดให้รุ่นน้องดูแลและพัฒนาต่อจากผม เป็นความรู้ที่สามารถใช้เรียนต่อในมหาลัย ไปต่อยอดสู่อาชีพได้\"\n\u003e หลังจบโครงการ:\n\u003e \"หลายๆคนมักจะบอกว่าการทำ OCR เป็นง่ายที่ง่าย ผมเห็นด้วยครับมันง่ายครับ แต่ทำไมกลับไม่มีใครที่คิดลงมือจะทำ? ทั้งๆที่ Tools ของมันครบคันมากๆ หลายๆที่ หลายๆบริษัทก็พยายามชูฟีเจอร์นี้ มันก็เหมือนกับการมีสูตรอาหารที่คุณชอบอยู่ในมือไม่ได้ด้อยกว่าใคร มีวัตถุดิบ ของทุกอย่างครบคัน ขาดแค่คนลงมือทำ แต่ก็ยังไปซื้ออาหารนั้นมาทานอยู่ประจำ ดังนั้นผมขอที่จะเป็นคนพัฒนา OCR เป็นพ่อครัวที่จะทำเมนู OCR Thai เพื่อให้ทุกคนมี Tools OCR Thai ที่ดีไปใช้งาน และเป็นการพัฒนาวงการนี้ให้ใหญ่ขึ้นอีกด้วยครับ\"","date":"2021-07-23","title":"TH National Document OCR (THND OCR) ","builder":"Kampanart Chaimooltan (Cop)","builder_info":"มัธยมศึกษาปีที่ 5 / เชียงใหม่","thumbnail":"/images/2021/020/01.jpg","links":{"github":"https://github.com/copninich/TH-National-Document-OCR/","facebook":"https://www.facebook.com/aibuildersx/posts/","blog":"https://copninich.medium.com/5a673cc8a686"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2021","id":"020-TH-National-Document-OCR-(THNDOCR)"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">A Lip Reader</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->พุทธคุณ บุญชัย (ข้าวตู)<!-- --> • </h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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ผมจึงอยากเข้าร่วมโครงการนี้เพื่อเรียนรู้การทำ AI ด้วย python และการใช้ library ต่างๆเช่น numpy หรือ pandas ผมเพิ่งมาเห็นโพสต์นี้เอาวันสุดท้ายก็อาจจะมีมีโค้ดผิดอยู่สองข้อ แต่ผมตั้งใจทำในระยะเวลาที่เหลืออยู่มากที่สุดแล้วครับ อยากเข้ามากๆครับ\"","date":"2-8-22","title":"A Lip Reader","builder":"พุทธคุณ บุญชัย (ข้าวตู)","builder_info":"","thumbnail":"/images/2022/53/01.jpg","links":{"github":"https://github.com/Kaotu999/A_Lip_Reader","facebook":"https://facebook.com/aibuildersx/posts/435685011933277","blog":"https://medium.com/@boonchaiphutthakhun/a-lip-reader-c69be0d8363c"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"A-Lip-Reader"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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จึงทำให้เกิดปัญหาที่ว่าร้านนำแมงดาที่มีพิษ(แมงดาถ้วย หรือแมงดาเหรา)นำมาปรุงอาหาร และขาย ซึ่งเกิดจากการเข้าใจผิด อาจทำให้ส่งผลต่อชีวิตได้ ผมจึงได้มีความสนใจที่จะสร้าง Application ในการแยกแยะประเภทของแมงดาจาน(กินได้) กับ แมงดาถ้วย(มีพิษ กินไม่ได้) เพื่อช่วยการตัดสินใจก่อนทำอาหาร เพื่อความปลอดภัยในการรับประทาน,\n- เก็บชุดข้อมูลจาก DuckDuckGo Image Search API; เริ่มแรก scrape ได้กว่า 1,000 รูปแต่คุณภาพไม่ดีจึงคัดเลือกด้วยมือและหาเพิ่มจนได้ชุดข้อมูลสุดท้ายที่แมงดาถ้วย 224 รูปและแมงดาจาน 226 รูป แบ่ง train-test split ที่ 85:15,\n- สร้าง annotation สำหรับ object detection ด้วยมือผ่านโปรแกรม LabelImg,\n- ปรับจูนโมเดลจากสถาปัตยกรรม VGG16, VGG19, AlexNet, ResNeXt50, DenseNet201 ครั้งแรกพบว่าผลบน test set ค่อนข้างแย่,\n- พบว่าโมเดลมีความสับสนระหว่างด้านหน้าและด้านหลังของแมงดา จึงทำโมเดลแยกสำหรับหน้า-หลัง; ได้ความแม่นยำสูงในการทายด้านหน้า-หลัง (F1 ~0.9),\n- หลังจากแยกแยะด้านหน้า-หลังแล้ว ใช้อีกโมเดลแยกประเภทซ้ำ (multi-model approach) ได้ผลดีขึ้น ด้านหน้า (F1 ~0.83) และ ด้านหลัง (F1 ~0.70); โมเดลที่ทำได้ดีที่สุดได้ผลในการจำแนกชนิดแมงดาโดยรวมสูงถึง F1 0.92,\n- โมเดลสุดท้ายคือ 1) object detection ทำนายว่าแมงดาอยู่ไหน 2) โมเดลทำนายว่าด้านหน้า-ด้านหลัง 3) ทำนายชนิดแมงดา,\n- ทดสอบเทียบกับมนุษย์ด้วยแบบสอบถามและรูป 16 รูป พบว่าโมเดลทำได้ดีกว่า (F1 0.89 vs 0.74); จำนวนตัวอย่างเล็กมาก ตีความอย่างระมัดระวัง\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เนื่องจากโรงเรียนของผมเป็นโรงเรียนวิทยาศาสตร์ทำให้ผมได้ทำโครงงานวิทยาศาสตร์ที่ต้องศึกษาหาความรู้ด้วยตนเองแล้วก็มีอาจารย์ครูที่ปรึกษามาแนะนำเกี่ยวกับโปรเจคการปรับปรุงน้ำดิบเพื่อนำมาผลิตน้ำประปา ที่ได้ผลิตน้ำประปาเองเป็นส่วนใหญ่เนื่องจากน้ำประปาที่ส่งมาจากการประปาไหลมาไม่เพียงพอต่อบุคคลในโรงเรียน โดยโรงเรียนได้มีการผลิตน้ำเองมาก่อนหน้านี้แล้ว แต่ยังพบว่าน้ำไม่ค่อยได้มาตราฐาน จึงทำให้ผมและคุณครูได้คิดที่จะทำเครื่อง Jartest (สามารถดูเพิ่มเติมได้ในผลงานครับ) ที่ใช้ในทดลองเพื่อหาปริมาณของสารเคมีที่เหมาะสมต่อการผลิตน้ำประปา และเมื่อทำเครื่องเสร็จผมพบกับปัญหาที่ว่า น้ำดิบมีคุณสมบัติไม่เหมือนกันตลอดทั้งวัน ทำให้ต้องมีการทำ Jartest 3 ครั้งต่อวันเพื่อปรับเปลี่ยนอัตราส่วนของสารเคมีให้เหมาะสมต่อการปรับปรุงน้ำดิบ ผมจึงได้หาข้อมูลต่อที่จะช่วยทำให้การปรับปรุงน้ำดิบได้รวดเร็วมากขึ้น ซึ่งเป็นการนำ deep learning มาประมวลผลข้อมูลทางสถิตจากข้อมูลก่อน-หลังการทดลองและปริมาณสารที่เติม และประมวลผลภาพของขนาดตะกอน แล้วผมก็มาพบกับโครงการ AI Builders ที่มีการอบรมเกี่ยวกับ Data Sci และ AI ซึ่งตอบโจทย์ต่อโปรเจคที่ผมสนใจเป็นอย่างมาก แล้วมีการประยุกต์องค์ความรู้ที่เรียนมาใช้ในการแก้ไขปัญหาในชีวิตประจำวันได้อีกด้วย ดูได้จากการนำเสนอผลงานของรุ่นที่แล้วมีความน่าสนใจมากครับ แล้วผมมั่นใจว่าโครงการจะมอบประสบการณ์และเทคนิคในการทำงานเกี่ยวกับAi ให้ผมอย่างมากครับากครับ จึงทำให้กระผมอยากเก็บเกี่ยวประสบการณ์เกี่ยว AI จากโครงการนี้ครับ\"","date":"19-7-22","title":"AI แยกแยะแมงดาจาน กับ แมงดาถ้วย","builder":"ภัคพล อาจบุราย 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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1v60ess">.css-1v60ess{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;position:absolute;white-space:nowrap;vertical-align:middle;outline:2px solid 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Auto Lyric Recognizer</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->กิตติพงศ์ เทพอยู่ (ปืน)<!-- --> • </h4><style data-emotion="css 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สำนักงานใหญ่อยู่ที่ เมนโลพาร์ก รัฐแคลิฟอร์เนีย เฟซบุ๊กก่อตั้งเมื่อวันพุธที่ 4 กุมภาพันธ์ ค.ศ. 2004, Output text: 1. เฟซบุ๊กคืออะไร A: บริการเครือข่ายสังคมสัญชาติอเมริกัน 2. เฟซบุ๊กก่อตั้งเมื่อไร A: วันที่ 4 กุมภาพันธ์ ค.ศ. 2004,\n- ใช้ชุดข้อมูล question answering (เอามากลับหัวกลับหางเป็น question generation) ได้แก่ XQuAD, Thai QA (SQuAD version), iapp-wiki-qa-dataset,\n- ทำความสะอาดข้อมูล เช่น HTML markup, ช่องว่างเกิน 1 ช่อง, วงเล็บที่ว่างเปล่า (ส่วนใหญ่เกิดกับบทความ Wikipedia); พบว่าหนึ่งบทความ (context) จะมีคำถามโดยทั่วไป 1-5 คำถาม,\n- เลือกใช้ mT5 ผ่าน Shivanandroy/simpleT5 เพื่อปรับจูนกับชุดข้อมูลที่มี; ใส่ seperator tokens (\u003cSEP\u003e และ \u003cตัวเลข\u003e) ระหว่างคำถามเพื่อไม่ให้โมเดลงงกับการสร้างคำถามหลายข้อ โดยเฉพาะการที่โมเดลสับสนเลขบอกข้อคำถาม (1. xxx 2. xxx) กับเลขทศนิยม (1.2 ล้านคน),\n- ทำ data augmentation โดยการแตกคำถามสำหรับบทความเดียวกันเป็นหลายตัวอย่าง เช่น บทความที่มี 10 คำถาม แทนที่จะเป็นหนึ่งตัวอย่าง แตกให้เป็น 2 ตัวอย่าง ตัวอย่างละ 5 คำถาม เป็นต้น; ทำให้ได้จำนวนคำถามเพิ่มจาก 4,500 ข้อเป็น 14,000 ข้อ,\n- วัดผลด้วยเกณฑ์อ้างอิงจากโครงงานคล้ายกัน patil-suraj/question_generation คือ METEOR, GLEU, BLEU-4, Chr-F, และ ROUGE-L; พบว่าโมเดลที่ใช้ data augmentation ทำคะแนนได้ดีที่สุด แต่มีปัญหาว่าไม่สามารถสร้างคำถามได้ตามจำนวนที่ต้องการนัก,\n- ตรวจว่าคำถาม-ตอบ 449 คู่ที่ถูกสร้างขึ้นมาสำหรับ validation set นั้นถูกต้องแค่นั้น **ด้วยมือ** พบว่าถูกประมาณ 70%; คู่คำถาม-ตอบที่ผิดแบ่งได้เป็น อ่านไม่รู้เรื่อง (37.7%), ไม่มีคำตอบ (15.2%), จำนวนคำถามไม่ตรงตามที่ต้องการ (8.7%), คำตอบผิด (13.8%), สร้างคำถามซ้ำ ( 24.6%)\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"I firmly stand by the fact that I have a passion for always seeking to learn and research new things and technologies to improve myself and the world around me.  \"One example of this was when I took the Harvard University CS50x course last year in grade 8. This programming course was extremely challenging. But with my passion and determination, I pressed on, excelled, and earned my certificate shown in the attached portfolio. Furthermore, I went on to completely self-study the AP Computer Science Principles course and was the only person who ever scored a perfect 5 out of 5 for my school. Currently, Im studying another Harvard course that focuses on artificial intelligence: CS50AI.\",  Another achievement was the application that I wrote for my school, which is being used by over 200 people. For context, I am the youngest Student Council member in the history of my school, and I wanted to help the community by combining all the news into one place. Please see the portfolio for links to the app. During this time, I also joined the AWS Builders program to learn about the platform and all the marvelous tools that it offers.  Additionally, I am also very familiar with Linux. Throughout the last 3 to 4 years, I have researched on my own about it and have learned enough about it to post an install guide on Youtube and help countless people. To make the installation straightforward, I created various packages to add support for the Microsoft Surface devices (https://github.com/parinzee/linux-surface-overlay).  Finally, I believe that I am a compelling candidate because of my experience, ability to self-study, and extreme perseverance. These are qualities that innovators and leaders need to have. Accepting me into this program would allow me to help Thailand effectively in the future.\"","date":"11-8-22","title":"Automatic E2E Thai Question Generation with MT5","builder":"ปรินทพัฒน์ เพ็งพันธุ์ (ปริน)","builder_info":"","thumbnail":"/images/2022/62/01.jpg","links":{"github":"https://parinzee.github.io/ThaiQuestionGenerationMT5/","facebook":"https://facebook.com/aibuildersx/posts/450060740495704","blog":"https://medium.com/@parinzee/studying-let-an-ai-generate-q-as-to-quiz-you-9ef27b1554d"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Automatic-E2E-Thai-Question-Generation-with-MT5"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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สำนักงานใหญ่อยู่ที่ เมนโลพาร์ก รัฐแคลิฟอร์เนีย เฟซบุ๊กก่อตั้งเมื่อวันพุธที่ 4 กุมภาพันธ์ ค.ศ. 2004, Output text: 1. เฟซบุ๊กคืออะไร A: บริการเครือข่ายสังคมสัญชาติอเมริกัน 2. เฟซบุ๊กก่อตั้งเมื่อไร A: วันที่ 4 กุมภาพันธ์ ค.ศ. 2004,\n- ใช้ชุดข้อมูล question answering (เอามากลับหัวกลับหางเป็น question generation) ได้แก่ XQuAD, Thai QA (SQuAD version), iapp-wiki-qa-dataset,\n- ทำความสะอาดข้อมูล เช่น HTML markup, ช่องว่างเกิน 1 ช่อง, วงเล็บที่ว่างเปล่า (ส่วนใหญ่เกิดกับบทความ Wikipedia); พบว่าหนึ่งบทความ (context) จะมีคำถามโดยทั่วไป 1-5 คำถาม,\n- เลือกใช้ mT5 ผ่าน Shivanandroy/simpleT5 เพื่อปรับจูนกับชุดข้อมูลที่มี; ใส่ seperator tokens (\u003cSEP\u003e และ \u003cตัวเลข\u003e) ระหว่างคำถามเพื่อไม่ให้โมเดลงงกับการสร้างคำถามหลายข้อ โดยเฉพาะการที่โมเดลสับสนเลขบอกข้อคำถาม (1. xxx 2. xxx) กับเลขทศนิยม (1.2 ล้านคน),\n- ทำ data augmentation โดยการแตกคำถามสำหรับบทความเดียวกันเป็นหลายตัวอย่าง เช่น บทความที่มี 10 คำถาม แทนที่จะเป็นหนึ่งตัวอย่าง แตกให้เป็น 2 ตัวอย่าง ตัวอย่างละ 5 คำถาม เป็นต้น; ทำให้ได้จำนวนคำถามเพิ่มจาก 4,500 ข้อเป็น 14,000 ข้อ,\n- วัดผลด้วยเกณฑ์อ้างอิงจากโครงงานคล้ายกัน patil-suraj/question_generation คือ METEOR, GLEU, BLEU-4, Chr-F, และ ROUGE-L; พบว่าโมเดลที่ใช้ data augmentation ทำคะแนนได้ดีที่สุด แต่มีปัญหาว่าไม่สามารถสร้างคำถามได้ตามจำนวนที่ต้องการนัก,\n- ตรวจว่าคำถาม-ตอบ 449 คู่ที่ถูกสร้างขึ้นมาสำหรับ validation set นั้นถูกต้องแค่นั้น **ด้วยมือ** พบว่าถูกประมาณ 70%; คู่คำถาม-ตอบที่ผิดแบ่งได้เป็น อ่านไม่รู้เรื่อง (37.7%), ไม่มีคำตอบ (15.2%), จำนวนคำถามไม่ตรงตามที่ต้องการ (8.7%), คำตอบผิด (13.8%), สร้างคำถามซ้ำ ( 24.6%)\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"I firmly stand by the fact that I have a passion for always seeking to learn and research new things and technologies to improve myself and the world around me.  \"One example of this was when I took the Harvard University CS50x course last year in grade 8. This programming course was extremely challenging. But with my passion and determination, I pressed on, excelled, and earned my certificate shown in the attached portfolio. Furthermore, I went on to completely self-study the AP Computer Science Principles course and was the only person who ever scored a perfect 5 out of 5 for my school. Currently, Im studying another Harvard course that focuses on artificial intelligence: CS50AI.\",  Another achievement was the application that I wrote for my school, which is being used by over 200 people. For context, I am the youngest Student Council member in the history of my school, and I wanted to help the community by combining all the news into one place. Please see the portfolio for links to the app. During this time, I also joined the AWS Builders program to learn about the platform and all the marvelous tools that it offers.  Additionally, I am also very familiar with Linux. Throughout the last 3 to 4 years, I have researched on my own about it and have learned enough about it to post an install guide on Youtube and help countless people. To make the installation straightforward, I created various packages to add support for the Microsoft Surface devices (https://github.com/parinzee/linux-surface-overlay).  Finally, I believe that I am a compelling candidate because of my experience, ability to self-study, and extreme perseverance. These are qualities that innovators and leaders need to have. Accepting me into this program would allow me to help Thailand effectively in the future.\"","date":"11-8-22","title":"Automatic E2E Thai Question Generation with MT5","builder":"ปรินทพัฒน์ เพ็งพันธุ์ (ปริน)","builder_info":"","thumbnail":"/images/2022/62/01.jpg","links":{"github":"https://parinzee.github.io/ThaiQuestionGenerationMT5/","facebook":"https://facebook.com/aibuildersx/posts/450060740495704","blog":"https://medium.com/@parinzee/studying-let-an-ai-generate-q-as-to-quiz-you-9ef27b1554d"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Automatic-E2E-Thai-Question-Generation-with-MT5"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">BACK (Blind All Can Know) - Action Captioning for Blinds</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->โชติวัฒน์ ตั้งสถาพร (ไนน์)<!-- --> • </h4><style data-emotion="css 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diff --git a/2022/Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram.html b/2022/Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram.html
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@@ -1 +1 @@
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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เลือกเพลงที่มีเสียงคนร้องเพลงไม่เกินร้อยละ 60 ของความยาวเพลง, หากมี voice sample แต่ยังมีช่วงที่มี beat หรือ melody เล่นอยู่ด้วยก็พอปล่อยผ่านได้, ทั้งเพลงควรมีความคงที่ของ BPM(Beat per minute) และ Time Signature หรือไม่ได้มีการเปลี่ยนแปลงที่ไม่บ่อยจนเกินไป; ได้เพลงที่ผ่านการทำความสะอาด 1,090 เพลงรวมเวลา 71.8 ชั่วโมง,\n- ใช้สถาปัตยกรรม Variational Autoencoder (VAE) เพื่อเรียนรู้การสร้าง spectogram ของเพลง EDM,\n- ประเมินคุณภาพด้วย mean opinion score (MOS) จากแบบสอบถาม คน ด้านความชัดเจนของ beat โดยรวม (2.67/5), ความชัดเจนของ melody โดยรวม (2.69/5) และความพึงพอใจโดยรวม (2.77/5),\n- มองแนวทางพัฒนาด้วยการเทรนให้นานขึ้น-ข้อมูลมากขึ้น, ใช้ช่วง climax ที่เมโลดี้ชัดเจนเทรน และลองสถาปัตยกรรมใหม่ๆ,\n- อัลบั้ม The Final of Chaos? (น่าจะ) เป็นอัลบั้ม EDM ที่สร้างโดยปัญญาประดิษฐ์แรกของไทย ลองฟังกันได้ที่: https://soundcloud.app.goo.gl/17SThr5PisKCFaZC6\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"กระผมเคยได้มีโอกาสในการร่วมเข้าการแข่งขันในงาน TMLCC เมื่อปี 2021 โดยที่ผมได้ช่วยเหลือในการนำ dataset มา clean และ select data ที่น่าสนใจนำไปใช้ใน algorithm มีแรงบันดาลใจที่จะเขียนโค้ดจากเพื่อนของผมที่แสดงให้เห็นถึงความสำคัญและศักยภาพของ AI ทำให้ผมได้ศึกษาและเรียนรู้การเขียนโค้ดมาเรื่อยๆในระยะเวลา 1 ปีที่ผ่านมานี้แต่ยังไม่ได้เริ่มเขียนโปรเจคแบบจริงๆจังๆสักครั้งเลยอยากจะลองทำดูในโครงการนี้ครับ  เหตุผลที่ผมอยากเข้าร่วมโครงการนี้เริ่มต้นมาจากการได้เห็นเพื่อนของผมคนหนึ่งที่ได้มีความสนใจในด้าน AI ได้ชวนผมมาทำโครงงานแข่งด้าน AI แล้วและยังเคยเข้าร่วมโครงการนี้ได้มาชวนผมให้มาลองศึกษาและเข้าใจการทำงานและการสร้าง AI อีกทั้งผมยังเคยได้เข้าค่ายแพทย์ของมหาลัยวิทยาลัยธรรมศาสตร์ โดยในค่ายนั้นได้มีการบรรยายเกี่ยวกับ Digital Hospital ในหัวข้อของ AI ทำให้ผมมีความสนใจในด้านนี้อยู่แล้วได้ตัดสินใจที่จะเข้าร่วมโครงการนี้ ทั้งนี้ผมเลยเห็นโครงการนี้เป็นโอกาสอันดีที่ควรจะคว้าไว้เพื่อต่อยอดในการศึกษาและการงานของผมในอาชีพแพทย์ได้ครับ  เพลงในโลกนี้มีมากกว่าที่จะนับได้ทั้งหมด ทั้งเป็นเพลงที่เป็นที่รู้จักกันอย่างดีหรือมีคนรู้จักเพียงหยิบมือ แต่ทั้งนี้เพลงก็จะถูกแบ่งประเภทด้วยสิ่งที่เรียกว่า Genre หากแต่เป็นเพียงสมัยก่อนยุคเพลง Digital การใช้หูฟังเพื่อแบ่งแยกนั้นอาจไม่ต้องการประสบการณ์ในการฟังเพลงที่มากนัก แต่กระนั้นเองยุคสมัยในการผสมผสานการทำเพลงแบบดิจิตอลก็เข้ามาถึงทำให้เกิดเพลงประเภทหนึ่งขึ้นมานั้นคือ Electronic Music แต่ส่วนมากเราจะได้ยินกันทั่วไปคือ EDM หรือ Electronic Dance Music อย่างไรก็ตาม electronic music นั้นเป็นเพลงที่เกิดขึ้นจากเสียงสังเคราะห์ทำให้เกิดความหลากหลายที่มากกว่าเดิมจากเพลงที่เกิดจากเครื่องดนตรีตามปกติทำให้เกิด genre และ subgenre ขึ้นมากมายและมีจำนวนเพิ่มขึ้นอย่างไม่หยุดอันเป็นเหตุทำให้ทำให้หลายบุคคลเกิดความสับสนและโต้แย้งกันถึง genre ของเพลงบางเพลงจนถึงวันนี้ ตัวอย่าง genre สามารถหาดูได้ทางนี้ https://www.reddit.com/r/electronicmusic/comments/dbxf5x/extremely_genre_specific_relectronicmusic/ ผมจึงมีความคิดที่จะทำ AI ที่สามารถรับไฟล์เพลง หรือถ้าเป็นไปได้ก็รับค่า input จากเพลงที่เล่นอยู่และบอก Genre ใหญ่ๆให้คนทั่วไปเข้าถึง Genre ของ EDM ได้มากขึ้น ส่วนชุดข้อมูลนั้นเราสามารถหาโหลดได้จาก Youtube, Spotify, Soundcloud, Mixcloud เป็นต้น\"","date":"14-7-22","title":"Chaos EDM: Generating EDM Song with VAE (Variational Autoencoder) Spectrogram","builder":"ณยศ สุวัฒโน (ไมค์กี้)","builder_info":"","thumbnail":"/images/2022/34/01.jpg","links":{"github":"https://github.com/Mikey8943/EDM-spectrogram-vae","facebook":"https://facebook.com/aibuildersx/posts/414621047373007","blog":"https://medium.com/@nayos.su/generating-edm-song-with-vae-variational-autoencoder-spectrogram-eb6dcd5fc4b8"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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เลือกเพลงที่มีเสียงคนร้องเพลงไม่เกินร้อยละ 60 ของความยาวเพลง, หากมี voice sample แต่ยังมีช่วงที่มี beat หรือ melody เล่นอยู่ด้วยก็พอปล่อยผ่านได้, ทั้งเพลงควรมีความคงที่ของ BPM(Beat per minute) และ Time Signature หรือไม่ได้มีการเปลี่ยนแปลงที่ไม่บ่อยจนเกินไป; ได้เพลงที่ผ่านการทำความสะอาด 1,090 เพลงรวมเวลา 71.8 ชั่วโมง,\n- ใช้สถาปัตยกรรม Variational Autoencoder (VAE) เพื่อเรียนรู้การสร้าง spectogram ของเพลง EDM,\n- ประเมินคุณภาพด้วย mean opinion score (MOS) จากแบบสอบถาม คน ด้านความชัดเจนของ beat โดยรวม (2.67/5), ความชัดเจนของ melody โดยรวม (2.69/5) และความพึงพอใจโดยรวม (2.77/5),\n- มองแนวทางพัฒนาด้วยการเทรนให้นานขึ้น-ข้อมูลมากขึ้น, ใช้ช่วง climax ที่เมโลดี้ชัดเจนเทรน และลองสถาปัตยกรรมใหม่ๆ,\n- อัลบั้ม The Final of Chaos? (น่าจะ) เป็นอัลบั้ม EDM ที่สร้างโดยปัญญาประดิษฐ์แรกของไทย ลองฟังกันได้ที่: https://soundcloud.app.goo.gl/17SThr5PisKCFaZC6\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"กระผมเคยได้มีโอกาสในการร่วมเข้าการแข่งขันในงาน TMLCC เมื่อปี 2021 โดยที่ผมได้ช่วยเหลือในการนำ dataset มา clean และ select data ที่น่าสนใจนำไปใช้ใน algorithm มีแรงบันดาลใจที่จะเขียนโค้ดจากเพื่อนของผมที่แสดงให้เห็นถึงความสำคัญและศักยภาพของ AI ทำให้ผมได้ศึกษาและเรียนรู้การเขียนโค้ดมาเรื่อยๆในระยะเวลา 1 ปีที่ผ่านมานี้แต่ยังไม่ได้เริ่มเขียนโปรเจคแบบจริงๆจังๆสักครั้งเลยอยากจะลองทำดูในโครงการนี้ครับ  เหตุผลที่ผมอยากเข้าร่วมโครงการนี้เริ่มต้นมาจากการได้เห็นเพื่อนของผมคนหนึ่งที่ได้มีความสนใจในด้าน AI ได้ชวนผมมาทำโครงงานแข่งด้าน AI แล้วและยังเคยเข้าร่วมโครงการนี้ได้มาชวนผมให้มาลองศึกษาและเข้าใจการทำงานและการสร้าง AI อีกทั้งผมยังเคยได้เข้าค่ายแพทย์ของมหาลัยวิทยาลัยธรรมศาสตร์ โดยในค่ายนั้นได้มีการบรรยายเกี่ยวกับ Digital Hospital ในหัวข้อของ AI ทำให้ผมมีความสนใจในด้านนี้อยู่แล้วได้ตัดสินใจที่จะเข้าร่วมโครงการนี้ ทั้งนี้ผมเลยเห็นโครงการนี้เป็นโอกาสอันดีที่ควรจะคว้าไว้เพื่อต่อยอดในการศึกษาและการงานของผมในอาชีพแพทย์ได้ครับ  เพลงในโลกนี้มีมากกว่าที่จะนับได้ทั้งหมด ทั้งเป็นเพลงที่เป็นที่รู้จักกันอย่างดีหรือมีคนรู้จักเพียงหยิบมือ แต่ทั้งนี้เพลงก็จะถูกแบ่งประเภทด้วยสิ่งที่เรียกว่า Genre หากแต่เป็นเพียงสมัยก่อนยุคเพลง Digital การใช้หูฟังเพื่อแบ่งแยกนั้นอาจไม่ต้องการประสบการณ์ในการฟังเพลงที่มากนัก แต่กระนั้นเองยุคสมัยในการผสมผสานการทำเพลงแบบดิจิตอลก็เข้ามาถึงทำให้เกิดเพลงประเภทหนึ่งขึ้นมานั้นคือ Electronic Music แต่ส่วนมากเราจะได้ยินกันทั่วไปคือ EDM หรือ Electronic Dance Music อย่างไรก็ตาม electronic music นั้นเป็นเพลงที่เกิดขึ้นจากเสียงสังเคราะห์ทำให้เกิดความหลากหลายที่มากกว่าเดิมจากเพลงที่เกิดจากเครื่องดนตรีตามปกติทำให้เกิด genre และ subgenre ขึ้นมากมายและมีจำนวนเพิ่มขึ้นอย่างไม่หยุดอันเป็นเหตุทำให้ทำให้หลายบุคคลเกิดความสับสนและโต้แย้งกันถึง genre ของเพลงบางเพลงจนถึงวันนี้ ตัวอย่าง genre สามารถหาดูได้ทางนี้ https://www.reddit.com/r/electronicmusic/comments/dbxf5x/extremely_genre_specific_relectronicmusic/ ผมจึงมีความคิดที่จะทำ AI ที่สามารถรับไฟล์เพลง หรือถ้าเป็นไปได้ก็รับค่า input จากเพลงที่เล่นอยู่และบอก Genre ใหญ่ๆให้คนทั่วไปเข้าถึง Genre ของ EDM ได้มากขึ้น ส่วนชุดข้อมูลนั้นเราสามารถหาโหลดได้จาก Youtube, Spotify, Soundcloud, Mixcloud เป็นต้น\"","date":"14-7-22","title":"Chaos EDM: Generating EDM Song with VAE (Variational Autoencoder) Spectrogram","builder":"ณยศ สุวัฒโน (ไมค์กี้)","builder_info":"","thumbnail":"/images/2022/34/01.jpg","links":{"github":"https://github.com/Mikey8943/EDM-spectrogram-vae","facebook":"https://facebook.com/aibuildersx/posts/414621047373007","blog":"https://medium.com/@nayos.su/generating-edm-song-with-vae-variational-autoencoder-spectrogram-eb6dcd5fc4b8"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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-<!DOCTYPE html><html><head><meta name="viewport" content="width=device-width"/><meta charSet="utf-8"/><link rel="apple-touch-icon" sizes="180x180" href="/showcase/favicon/apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="/showcase/favicon/favicon-32x32.png"/><link rel="icon" type="image/png" sizes="16x16" href="/showcase/favicon/favicon-16x16.png"/><link rel="manifest" href="/showcase/favicon/site.webmanifest"/><link rel="mask-icon" href="/showcase/favicon/safari-pinned-tab.svg" color="##5bbad5"/><link rel="shortcut icon" href="/showcase/favicon/favicon.ico"/><meta name="msapplication-TileColor" content="##5bbad5"/><meta name="msapplication-config" content="/showcase/favicon/browserconfig.xml"/><meta name="theme-color" content="#ffffff"/><title>Crossec : ระบบส่งเสริมการทำปฏิบัติการเนื้อเยื่อพืชด้วยปัญญาประดิษฐ์</title><meta name="twitter:card" content="summary"/><meta property="og:title" content="Crossec : 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เพราะตรวจสอบชิ้นงานได้ตลอดเวลา และสามารถศึกษาหัวข้อเนื่อเยื่อพืชที่ตนเองสนใจได้ ทำให้นักเรียนได้เห็นเนื้อเยื่อของพืชหลากหลายชนิดจากนักเรียน คนอื่น ๆ จากการสังเกตและเชื่อมโยงภาพเหล่านั้นจะทำให้นักเรียนสามารถสร้างข้อสรุปและสร้างองค์ความรู้ได้ด้วยตนเอง (constructivisim) นอกจากนี้ยังเป็นเครื่องมือที่อำนวยความสะดวกให้ครูจัดการเรียนรู้ด้วยวิธีปฏิบัติจริง (active learning) อีกด้วย  Dataset สามารถหาได้จากการทำปฏิบัติการเนื้อเยื่อพืชของนักเรียนหรือสร้างขึ้นเอง\"","date":"31-7-22","title":"Crossec : ระบบส่งเสริมการทำปฏิบัติการเนื้อเยื่อพืชด้วยปัญญาประดิษฐ์","builder":"วิทวัส กิติภัทร์ถาวร 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diff --git "a/2022/Debunker-ML-\340\270\225\340\270\243\340\270\247\340\270\210\340\270\210\340\270\261\340\270\232\340\270\202\340\271\210\340\270\262\340\270\247\340\270\245\340\270\247\340\270\207.html" "b/2022/Debunker-ML-\340\270\225\340\270\243\340\270\247\340\270\210\340\270\210\340\270\261\340\270\232\340\270\202\340\271\210\340\270\262\340\270\247\340\270\245\340\270\247\340\270\207.html"
index dcefc16..ae698c5 100644
--- "a/2022/Debunker-ML-\340\270\225\340\270\243\340\270\247\340\270\210\340\270\210\340\270\261\340\270\232\340\270\202\340\271\210\340\270\262\340\270\247\340\270\245\340\270\247\340\270\207.html"
+++ "b/2022/Debunker-ML-\340\270\225\340\270\243\340\270\247\340\270\210\340\270\210\340\270\261\340\270\232\340\270\202\340\271\210\340\270\262\340\270\247\340\270\245\340\270\247\340\270\207.html"
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Debunker: ML ตรวจจับข่าวลวง</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->นิธิวัฒน์ สิริรัตนชัยกุล (ตง)<!-- --> • </h4><style data-emotion="css 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diff --git a/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model.html b/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model.html
index c888370..b77ef9e 100644
--- a/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model.html
+++ b/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model.html
@@ -1 +1 @@
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image กับ DuckDuckgo แล้วทำการคัดแยกข้อมูลด้วยมืออีกรอบ (1,500 รูป) ; ส่วนของบัตรประชาชน ใช้ Rules-based programming. (Selection + Edit distance) คู่กับ OCR (Optical Character Recognition) ในการตรวจจับ ชื่อ-นามสกุล และ เลขบัตรประชาชน เนื่องจากไม่สามารถหา Dataset ได้ T T,\n- ข้อมูลแบ่งเป็น Train set : 1,000 รูป , Validation / Test set : อย่างละ 250 รูป,\n- เทรนโมเดล Efficientdet_d2 (Object detection) ด้วย Google Colab Pro,\n- ได้ accuracy และ F1Score ที่ประมาณ 99.51 % บนชุดข้อมูล Validation set และ 94.00 % บนชุดข้อมูล Test set,\n- ศึกษาคุณภาพโมเดลด้วยให้คนจำนวน 15 คน ทดลองบันทึกผลตรวจ ATK ควบคู่กับ ชื่อ-นามสกุล, เลขบัตรประชาชนด้วยตัวเอง และ ทดลองใช้บน Webapp พบว่ามีประสิทธิภาพที่มากกว่า และ ใช้ระยะเวลาที่น้อยกว่าในการบันทึก และ แยกแยะข้อมูลด้วยตัวเอง,\n- พบว่าโมเดลยังมีข้อบกพร่องในกรณีที่เป็นตัวอักษร “i” (อักษรไอตัวเล็ก) กับ “l” (อักษรแอลตัวเล็ก) ที่ชื่อ-นามสกุล ของบัตรประชาชน โมเดลยังมีโอกาสตรวจจับผิดพลาดได้อยู่ (เกิดขึ้นสามในสิบครั้งโดยเฉลี่ย) ; แก้ไขได้ด้วยการทำ prediction model อักษร (i, l) [พัฒนาต่อในอนาคต],\n- ในกรณีที่ที่ตรวจ ATK สีมีความจางมาก หรือ มีแสงรบกวนเข้ามาในรูปภาพ อาจทำให้โมเดลตรวจจับผิดพลาดได้ ; แก้ไขได้โดยการถ่ายภาพใหม่ หรือ เปลี่ยนที่ตรวจ ATK ใหม่ และ หา Dataset เพิ่ม [พัฒนาต่อในอนาคต],\n- โดยในอนาคตจะพัฒนาให้ใช้ได้ในระบบ Line หรือ Application เพื่อให้โมเดลสามารถใช้งานได้จริงในการคัดกรอง และ บันทึกผลตรวจเชื้อ COVID-19 ในสถานศึกษา หรือ ในหน่วยงานต่างๆในอนาคต, ** ตอนนี้เปิดให้ทดลองใช้บน Webapp [กรณีพบเจอปัญหา หรือ อยากให้คำแนะนำสามารถ report มาใน Webapp ได้เลยย…. O w O\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"แรงบันดาลใจมาจาก ตอนที่ผมได้เข้าร่วมกิจกรรมในงานของ Kidbright AI Bot ครับ ตอนนั้นเป็นครั้งแรกที่ผมได้รู้จักและเข้าใจภาพรวมในเรื่องของ AI และกระบวนการโดยรวมครับ จากพี่ๆที่โครงการมาอบรมให้ครับ ผมเลยได้ลองสร้าง, เทรน model และ เขียนโค้ดที่เป็น AI โดยใช้ Kidbright AI Platform ครั้งแรกโดยการสั่งการให้หุ่นยนต์เดินด้วยเสียงได้ครับ หลังจากนั้นผมจึงมีความคิดที่อยากทำโครงการที่ใช้ AI ในการประมวลผลขึ้นมาจริงๆครับ ผมเคยเข้าร่วมโครงการ Super AI Engineer เมื่อ 2 ปีที่แล้วครับแต่ตอนนั้นผมยังไม่มีพื้นฐานในเรื่องของ Coding กับ Math เลยไม่ผ่านรอบต่อไปที่ทำ AI ครับ หลังจากนั้นผมจึงกลับไปฝึกพื้นฐาน Coding ที่เป็น Python, Pandas, Numpy มาเลยพอมีพื้นฐานระดับนึงแล้วครับ แล้วก็คิดจะลองทำโปรเจคที่เป็น AI ดูแต่ผมก็ไม่ค่อยเข้าใจเลยไม่กล้าทำขึ้นมาทีครับ หลังจากที่ผมรู้ว่ามีโครงการ AI Builder ผมเลยสนใจที่อยากเข้าร่วมโครงการเพราะผมว่าตอนนี้ผมมีความพร้อมมากกว่ารอบที่แล้ว และ ผมมีความมั่นใจมากกว่าที่แล้ว และ ก็ผมคิดว่าถ้าผมได้เข้าทำโครงการนี้จริงๆแล้ว ผมจะได้มีเพื่อนๆ และ พี่ๆที่มีประสบการณ์ในการปรึกษา และ เรียนรู้ได้ครับ  เนื่องจากผมเคยทำ project ที่เขียน coding มาบ้างครับเลยได้รู้จักในเรื่องของ AI ครับแต่ยังไม่เคยทำแบบจริงๆจังๆด้วยตัวเองมาก่อนครับ เพราะ ไม่เข้าใจเรื่องหลักการแบบจริงๆจังๆรู้แต่คร่าวๆครับเคยแต่ใช้ในรูปของ platform ครับ เลยสนใจที่อยากจะเข้าโครงการนี้เพราะจากที่ผมศึกษามามีการสอนพื้นฐานต่างๆ ในการสร้าง AI มี Workshop ต่างๆ ได้ทำและพัฒนาผลงานจริงๆ ผมจึงอยากที่จะเข้าร่วมโครงการครับ  โครงงานที่ผมอยากทำเป็น การตรวจเอกสารยืนยันผลเชื้อของไวรัส Covid 19 ครับ โดยเป็นการ detection จากเอกสารว่า คนๆนี้ ชื่อ นามสกุล ผลตรวจติดเชื้อหรือไม่ ตรวจจากสถานที่ใด โดยสามารถทำได้ 2 แบบ 1. ส่งไฟล์ รูปภาพเข้ามาในระบบ กับ 2.ในสถานที่จริงให้เอาเอกสารยื่นเข้ากล้องให้ตรวจจับ หรือ เป็นตัวที่ตรวจสีขาวที่เป็นขีด โดยแนบคู่กับบัตรประชาชนครับ โดยจะแสดงผลว่าติดเชื้อหรือไม่ และก็จะเข้าระบบใน google sheet เป็น .csv เพื่อใช้ pandas ในการจัดการข้อมูลต่างๆได้ครับ เนื่องจากล่าสุดผมได้คุมสอบของนักศึกษาแพทย์ กสพท โดยที่คนที่จะเข้าสอบมีจำนวนเกือบถึง 5000 คนครับ โดยต้องตรวจสอบเอกสารการตรวจเชื้อของทุกๆคนด้วยตวเอง ทำให้เกิดโอกาสผิดพลาด และ คลาดเคลื่อนสูงครับ ถ้ามีระบบที่เป็น AI วิเคราะห์ได้ก็จะแก้ปัญหาในเรื่องของระยะเวลาในการตรวจเอกสาร, จำนวนของเจ้าหน้าที่คุมสอบ และ สถานการแออัดในสถานที่นั้นๆได้ครับ และ สามารถใช้ได้ทุกสถานที่ เช่น สนามสอบ, สถานศึกษาที่ต้องใช้ตรวจเอกสารผลเชื้อ covid 19 ครับ โดยชุดข้อมูลที่ใช้ในการเทรน หาได้จากใน internet (keyword == เอกสารตรวจโควิด, รูปแบบเอกสาร ผลการตรวจ covid) ส่วนถ้าเป็นเครื่องตรวจก็จะเทรนขีด (keyword == covid antigen test results, ) แสดงผลครับรูปแบบของเครื่องตรวจแบบต่างๆ โดยจะเอารูปแบบของเอกสาร และ เครื่องตรวจให้มีความหลากหลายเพื่อไม่ให้เกิดความผิดพลาดครับ\"","date":"4-8-22","title":"Detect and collect COVID-19 data more faster by using ATK-OCR Classification (AOC) model","builder":"ธนอนันท์ เฉลิมพันธ์ (เอ็ม)","builder_info":"","thumbnail":"/images/2022/55/01.jpg","links":{"github":"https://github.com/Tanaanan/AOC_ATK_OCR_Classification","facebook":"https://facebook.com/aibuildersx/posts/437047961796982","blog":"www.shorturl.at/apGX5"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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(Selection + Edit distance) คู่กับ OCR (Optical Character Recognition) ในการตรวจจับ ชื่อ-นามสกุล และ เลขบัตรประชาชน เนื่องจากไม่สามารถหา Dataset ได้ T T,\n- ข้อมูลแบ่งเป็น Train set : 1,000 รูป , Validation / Test set : อย่างละ 250 รูป,\n- เทรนโมเดล Efficientdet_d2 (Object detection) ด้วย Google Colab Pro,\n- ได้ accuracy และ F1Score ที่ประมาณ 99.51 % บนชุดข้อมูล Validation set และ 94.00 % บนชุดข้อมูล Test set,\n- ศึกษาคุณภาพโมเดลด้วยให้คนจำนวน 15 คน ทดลองบันทึกผลตรวจ ATK ควบคู่กับ ชื่อ-นามสกุล, เลขบัตรประชาชนด้วยตัวเอง และ ทดลองใช้บน Webapp พบว่ามีประสิทธิภาพที่มากกว่า และ ใช้ระยะเวลาที่น้อยกว่าในการบันทึก และ แยกแยะข้อมูลด้วยตัวเอง,\n- พบว่าโมเดลยังมีข้อบกพร่องในกรณีที่เป็นตัวอักษร “i” (อักษรไอตัวเล็ก) กับ “l” (อักษรแอลตัวเล็ก) ที่ชื่อ-นามสกุล ของบัตรประชาชน โมเดลยังมีโอกาสตรวจจับผิดพลาดได้อยู่ (เกิดขึ้นสามในสิบครั้งโดยเฉลี่ย) ; แก้ไขได้ด้วยการทำ prediction model อักษร (i, l) [พัฒนาต่อในอนาคต],\n- ในกรณีที่ที่ตรวจ ATK สีมีความจางมาก หรือ มีแสงรบกวนเข้ามาในรูปภาพ อาจทำให้โมเดลตรวจจับผิดพลาดได้ ; แก้ไขได้โดยการถ่ายภาพใหม่ หรือ เปลี่ยนที่ตรวจ ATK ใหม่ และ หา Dataset เพิ่ม [พัฒนาต่อในอนาคต],\n- โดยในอนาคตจะพัฒนาให้ใช้ได้ในระบบ Line หรือ Application เพื่อให้โมเดลสามารถใช้งานได้จริงในการคัดกรอง และ บันทึกผลตรวจเชื้อ COVID-19 ในสถานศึกษา หรือ ในหน่วยงานต่างๆในอนาคต, ** ตอนนี้เปิดให้ทดลองใช้บน Webapp [กรณีพบเจอปัญหา หรือ อยากให้คำแนะนำสามารถ report มาใน Webapp ได้เลยย…. O w O\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"แรงบันดาลใจมาจาก ตอนที่ผมได้เข้าร่วมกิจกรรมในงานของ Kidbright AI Bot ครับ ตอนนั้นเป็นครั้งแรกที่ผมได้รู้จักและเข้าใจภาพรวมในเรื่องของ AI และกระบวนการโดยรวมครับ จากพี่ๆที่โครงการมาอบรมให้ครับ ผมเลยได้ลองสร้าง, เทรน model และ เขียนโค้ดที่เป็น AI โดยใช้ Kidbright AI Platform ครั้งแรกโดยการสั่งการให้หุ่นยนต์เดินด้วยเสียงได้ครับ หลังจากนั้นผมจึงมีความคิดที่อยากทำโครงการที่ใช้ AI ในการประมวลผลขึ้นมาจริงๆครับ ผมเคยเข้าร่วมโครงการ Super AI Engineer เมื่อ 2 ปีที่แล้วครับแต่ตอนนั้นผมยังไม่มีพื้นฐานในเรื่องของ Coding กับ Math เลยไม่ผ่านรอบต่อไปที่ทำ AI ครับ หลังจากนั้นผมจึงกลับไปฝึกพื้นฐาน Coding ที่เป็น Python, Pandas, Numpy มาเลยพอมีพื้นฐานระดับนึงแล้วครับ แล้วก็คิดจะลองทำโปรเจคที่เป็น AI ดูแต่ผมก็ไม่ค่อยเข้าใจเลยไม่กล้าทำขึ้นมาทีครับ หลังจากที่ผมรู้ว่ามีโครงการ AI Builder ผมเลยสนใจที่อยากเข้าร่วมโครงการเพราะผมว่าตอนนี้ผมมีความพร้อมมากกว่ารอบที่แล้ว และ ผมมีความมั่นใจมากกว่าที่แล้ว และ ก็ผมคิดว่าถ้าผมได้เข้าทำโครงการนี้จริงๆแล้ว ผมจะได้มีเพื่อนๆ และ พี่ๆที่มีประสบการณ์ในการปรึกษา และ เรียนรู้ได้ครับ  เนื่องจากผมเคยทำ project ที่เขียน coding มาบ้างครับเลยได้รู้จักในเรื่องของ AI ครับแต่ยังไม่เคยทำแบบจริงๆจังๆด้วยตัวเองมาก่อนครับ เพราะ ไม่เข้าใจเรื่องหลักการแบบจริงๆจังๆรู้แต่คร่าวๆครับเคยแต่ใช้ในรูปของ platform ครับ เลยสนใจที่อยากจะเข้าโครงการนี้เพราะจากที่ผมศึกษามามีการสอนพื้นฐานต่างๆ ในการสร้าง AI มี Workshop ต่างๆ ได้ทำและพัฒนาผลงานจริงๆ ผมจึงอยากที่จะเข้าร่วมโครงการครับ  โครงงานที่ผมอยากทำเป็น การตรวจเอกสารยืนยันผลเชื้อของไวรัส Covid 19 ครับ โดยเป็นการ detection จากเอกสารว่า คนๆนี้ ชื่อ นามสกุล ผลตรวจติดเชื้อหรือไม่ ตรวจจากสถานที่ใด โดยสามารถทำได้ 2 แบบ 1. ส่งไฟล์ รูปภาพเข้ามาในระบบ กับ 2.ในสถานที่จริงให้เอาเอกสารยื่นเข้ากล้องให้ตรวจจับ หรือ เป็นตัวที่ตรวจสีขาวที่เป็นขีด โดยแนบคู่กับบัตรประชาชนครับ โดยจะแสดงผลว่าติดเชื้อหรือไม่ และก็จะเข้าระบบใน google sheet เป็น .csv เพื่อใช้ pandas ในการจัดการข้อมูลต่างๆได้ครับ เนื่องจากล่าสุดผมได้คุมสอบของนักศึกษาแพทย์ กสพท โดยที่คนที่จะเข้าสอบมีจำนวนเกือบถึง 5000 คนครับ โดยต้องตรวจสอบเอกสารการตรวจเชื้อของทุกๆคนด้วยตวเอง ทำให้เกิดโอกาสผิดพลาด และ คลาดเคลื่อนสูงครับ ถ้ามีระบบที่เป็น AI วิเคราะห์ได้ก็จะแก้ปัญหาในเรื่องของระยะเวลาในการตรวจเอกสาร, จำนวนของเจ้าหน้าที่คุมสอบ และ สถานการแออัดในสถานที่นั้นๆได้ครับ และ สามารถใช้ได้ทุกสถานที่ เช่น สนามสอบ, สถานศึกษาที่ต้องใช้ตรวจเอกสารผลเชื้อ covid 19 ครับ โดยชุดข้อมูลที่ใช้ในการเทรน หาได้จากใน internet (keyword == เอกสารตรวจโควิด, รูปแบบเอกสาร ผลการตรวจ covid) ส่วนถ้าเป็นเครื่องตรวจก็จะเทรนขีด (keyword == covid antigen test results, ) แสดงผลครับรูปแบบของเครื่องตรวจแบบต่างๆ โดยจะเอารูปแบบของเอกสาร และ เครื่องตรวจให้มีความหลากหลายเพื่อไม่ให้เกิดความผิดพลาดครับ\"","date":"4-8-22","title":"Detect and collect COVID-19 data more faster by using ATK-OCR Classification (AOC) model","builder":"ธนอนันท์ เฉลิมพันธ์ (เอ็ม)","builder_info":"","thumbnail":"/images/2022/55/01.jpg","links":{"github":"https://github.com/Tanaanan/AOC_ATK_OCR_Classification","facebook":"https://facebook.com/aibuildersx/posts/437047961796982","blog":"www.shorturl.at/apGX5"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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@@ -1 +1 @@
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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Others, Surprise) จากรูปหน้า,\n- Micro-expression เป็นการแสดงอารมณ์ที่รู้สึกจริง ๆ แต่ต้องโกหกเอาไว้ และเกิดขึ้นเร็วมากจนมนุษย์ทั่วไปไม่สามารถรับรู้ได้เลย ถ้าสมมติมีโมเดลที่สามารถตรวจและระบุอารมณ์นี้ได้อย่างแม่นยำ ก็จะสามารถจับอารมณ์ที่โกหกอยู่ได้และมีประโยชน์เป็นอย่างมากเช่นการจับโกหกในการนำไปเป็นพยานหลักฐานของสืบสวนคดีต่าง ๆ,\n- ใช้ชุดข้อมูล SAMM dataset ประกอบไปด้วยรูปภาพที่แคปมาจากวิดีโอที่ถ่ายด้วยกล้องความเร็ว 200 fps มีทั้งหมด 29 subjects 159 samples แต่ละ sample มีรูปประมาณ 30-100 รูป,\n- ดูตัวอย่าง micro expression ได้ที่ https://www.facebook.com/aibuildersx/videos/1455685481578809,\n- ชุดข้อมูลมี 7 อารมณ์ ได้แก่ Happiness, Sadness, Anger, Disgust, Contempt, Fear และ Other แต่ Sadness, Fear และ Disgust มีจำนวนรูปน้อยเกินไปจึงตัดออกเพื่อป้องกัน label imbalance,\n- แต่ละเฟรมของชุดข้อมูลถูกจดไว้ว่าเป็น Onset frame (หมายเลขเฟรมที่เริ่มอัดคลิป), Apex frame (หมายเลขเฟรมที่เป็นจุดพีคของการเกิด micro-expression), Offset frame (หมายเลขเฟรมที่จบการอัดคลิป) และ Duration (จำนวนเฟรมที่จับได้ ซึ่งสอดคล้องกับจำนวนรูปในไฟล์),\n- จัดการแปลงรูปเพื่อเข้าสู่โมเดล 4 รูปแบบคือ 1) Original Apex frame — ใช้เฟรม ณ จุด Apex มาเป็น input 2) Difference of Apex frame and Onset frame — เนื่องด้วยเราได้แปลงข้อมูลภาพของเราเป็นตัวเลขเมื่อนำเข้าโมเดล จึงลองเอาผลต่างของ Apex กับ Onset มาเป็น input เพื่อแสดงว่าภาพตอนพีคกับตอนเริ่มต่างกันยังไง 3) Optical flow of Apex frame and Onset frame — เปลี่ยนจากผลต่างตัวเลขของ 2 เฟรมมาเป็น Optical flow ซึ่งก็คือแพทเทิร์นการขยับของภาพ โดยจะแสดงเป็นกลุ่มการไหลของแสง 4) Optical flow of Apex frame and Onset frame + Original Apex frame — คือการนำทั้ง Optical flow เมื่อกี้และภาพของ input แบบที่ 1 มารวมกันและนำไปเป็น input,\n- เลือกใช้ ResNet-18 ที่ pretrained มาจาก EfficientFace ซึ่งเทรนมาจาก MS-Celeb-1M และมีจำนวน class มากถึง 12,666 คน,\n- สร้างแบบทดสอบ 10 หน้าจากรูปที่ไม่ได้ใช้เทรนโมเดล โมเดลตอบถูก 6 จาก 10 ข้อเทียบกับมนุษย์ 29 คนที่ตอบถูก 2.759 ข้อโดยเฉลี่ย,\n- ปัญหาที่พบและน่าทำการแก้ไขในอนาคต 1) จำนวนข้อมูลที่มีน้อย 2) ความ Imbalance ของข้อมูลในแต่ละ class 3) sample บางคลิป แทบไม่ขยับหรือขยับน้อยมาก 4) sample บางคลิป มีตำแหน่งหน้า ที่ไม่ตรงกันใน Apex frame กับ Onset frame ทำให้ optical flow ฟุ้งกระจาย\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมเคยมีประสบการณ์ในด้านนี้ตอนแข่ง TMLCC ครับ แต่ว่าก็ยังเป็นแค่สร้างโมเดลเพื่อใช้ในการแข่ง ซึ่งตอนนั้นผมรู้สึกว่ามันเพลินมากตอนสร้างโมเดล อาจจะมีเหนื่อยบ้างนิดหน่อยตอนที่ต้องอ่าน papers ยาว ๆ หลายสิบหน้าที่เกี่ยวกับเคมี แต่เราก็ต้องสู้ครับ! ฮ่าๆ แม้ว่าตอนแก้และรันแต่ละครั้ง accuracy จะขึ้นหรือลง แต่ผมก็รู้สึกสนุกและลุ้นไปกับมันทุกครั้งเลยครับ ถ้าจะให้บอกว่าแรงบันดาลใจในเรื่อง AI ของผมมาจากไหน ก็คงต้องบอกว่ามาจากตัวเองที่มึความสุขกับมันนี่แหละครับ  ตั้งแต่ประถม ผมเริ่มรู้สึกกับตัวเองว่าเรามีความสุขเวลาที่เราสามารถแก้ปัญหาต่าง ๆ ได้ (แน่นอนว่าใครก็ต้องมีความสุขแหละครับที่คิดหาทางแก้ปัญหาออกได้) นั่นจึงทำให้วิชาที่โดดเด่นในเรื่องของการแก้ปัญหาอย่างคณิตศาสตร์เป็นวิชาที่ผมชอบได้อย่างไม่ยากเลยครับ ผมรู้สึกมีความสุขและสนุกที่หาวิธีคิดออกโดยเฉพาะวิธีแปลก ๆ ที่คนอื่นเขาไม่คิดกัน จนม.ต้น ผมได้รู้จักกับการ coding ตั้งแต่ครั้งแรกที่ผมเริ่มโค้ดก็รู้เลยครับว่านี่แหละสิ่งที่เหมาะกับเรา จนมาตอนม.ปลาย ผมก็เริ่มมองตัวเองในอนาคตว่าเราจะทำอะไร ก็หาข้อมูลกับลองเขียนนู่นนี่นั่นเล่นๆ จนผมได้มาเจอกับ AI ความรู้สึกตอนเจอคือแบบเดียวกับตอนม.ต้นเลยครับ ก็รู้เลยว่านี่คือสิ่งที่เรากำลังตามหาอยู่ แต่ตั้งแต่ตอนนั้นผมก็ยังไม่ได้สัมผัสเลยว่า โปรเจค AI จริง ๆ เป็นแบบไหน กระบวนการในการทำโปรเจคที่แท้จริงเป็นอย่างไร จึงอยากเข้าร่วมโครงการนี้เพื่อที่จะได้รับประสบการณ์ในการทำโปรเจคที่เป็นชิ้นเป็นอันและได้รับความรู้ในด้านที่เกี่ยวข้องเพื่อที่จะไปเรียนรู้ต่อและนำมาพัฒนาตนเองขึ้นไปอีกครับ และผมยังอยากหาเพื่อนหรือกลุ่มคนที่สนใจในด้านเดียวกัน จะได้มีคนที่คุยเรื่องพวกนี้ด้วยได้ครับ\"","date":"10-8-22","title":"Emotion Detection from Facial Micro-experessions","builder":"ครองภพ มั่นคง 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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Others, Surprise) จากรูปหน้า,\n- Micro-expression เป็นการแสดงอารมณ์ที่รู้สึกจริง ๆ แต่ต้องโกหกเอาไว้ และเกิดขึ้นเร็วมากจนมนุษย์ทั่วไปไม่สามารถรับรู้ได้เลย ถ้าสมมติมีโมเดลที่สามารถตรวจและระบุอารมณ์นี้ได้อย่างแม่นยำ ก็จะสามารถจับอารมณ์ที่โกหกอยู่ได้และมีประโยชน์เป็นอย่างมากเช่นการจับโกหกในการนำไปเป็นพยานหลักฐานของสืบสวนคดีต่าง ๆ,\n- ใช้ชุดข้อมูล SAMM dataset ประกอบไปด้วยรูปภาพที่แคปมาจากวิดีโอที่ถ่ายด้วยกล้องความเร็ว 200 fps มีทั้งหมด 29 subjects 159 samples แต่ละ sample มีรูปประมาณ 30-100 รูป,\n- ดูตัวอย่าง micro expression ได้ที่ https://www.facebook.com/aibuildersx/videos/1455685481578809,\n- ชุดข้อมูลมี 7 อารมณ์ ได้แก่ Happiness, Sadness, Anger, Disgust, Contempt, Fear และ Other แต่ Sadness, Fear และ Disgust มีจำนวนรูปน้อยเกินไปจึงตัดออกเพื่อป้องกัน label imbalance,\n- แต่ละเฟรมของชุดข้อมูลถูกจดไว้ว่าเป็น Onset frame (หมายเลขเฟรมที่เริ่มอัดคลิป), Apex frame (หมายเลขเฟรมที่เป็นจุดพีคของการเกิด micro-expression), Offset frame (หมายเลขเฟรมที่จบการอัดคลิป) และ Duration 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ของข้อมูลในแต่ละ class 3) sample บางคลิป แทบไม่ขยับหรือขยับน้อยมาก 4) sample บางคลิป มีตำแหน่งหน้า ที่ไม่ตรงกันใน Apex frame กับ Onset frame ทำให้ optical flow ฟุ้งกระจาย\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมเคยมีประสบการณ์ในด้านนี้ตอนแข่ง TMLCC ครับ แต่ว่าก็ยังเป็นแค่สร้างโมเดลเพื่อใช้ในการแข่ง ซึ่งตอนนั้นผมรู้สึกว่ามันเพลินมากตอนสร้างโมเดล อาจจะมีเหนื่อยบ้างนิดหน่อยตอนที่ต้องอ่าน papers ยาว ๆ หลายสิบหน้าที่เกี่ยวกับเคมี แต่เราก็ต้องสู้ครับ! ฮ่าๆ แม้ว่าตอนแก้และรันแต่ละครั้ง accuracy จะขึ้นหรือลง แต่ผมก็รู้สึกสนุกและลุ้นไปกับมันทุกครั้งเลยครับ ถ้าจะให้บอกว่าแรงบันดาลใจในเรื่อง AI ของผมมาจากไหน ก็คงต้องบอกว่ามาจากตัวเองที่มึความสุขกับมันนี่แหละครับ  ตั้งแต่ประถม ผมเริ่มรู้สึกกับตัวเองว่าเรามีความสุขเวลาที่เราสามารถแก้ปัญหาต่าง ๆ ได้ (แน่นอนว่าใครก็ต้องมีความสุขแหละครับที่คิดหาทางแก้ปัญหาออกได้) นั่นจึงทำให้วิชาที่โดดเด่นในเรื่องของการแก้ปัญหาอย่างคณิตศาสตร์เป็นวิชาที่ผมชอบได้อย่างไม่ยากเลยครับ 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Food Ingredients Label Reader for Food Allergy</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->พีรณัฐ เมฆวิศิษฏ์ (ปอนด์)<!-- --> • </h4><style data-emotion="css 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index dde31eb..a355836 100644
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Deep Learning"/><meta property="og:description" content="หิรัญกุล พิมพ์ศิริ (ไกด์) • "/><meta property="og:image" content="https://ai-builders.github.io/showcase/images/2022/59/01.jpg"/><meta property="og:site_name" content="AI Builders Showcase"/><meta name="next-head-count" content="17"/><link rel="preload" href="/showcase/_next/static/css/f9f072bebc05078a.css" as="style"/><link rel="stylesheet" href="/showcase/_next/static/css/f9f072bebc05078a.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/showcase/_next/static/chunks/polyfills-5cd94c89d3acac5f.js"></script><script src="/showcase/_next/static/chunks/webpack-74b12628e711d77e.js" defer=""></script><script src="/showcase/_next/static/chunks/framework-5f4595e5518b5600.js" defer=""></script><script src="/showcase/_next/static/chunks/main-e95b58999d220b83.js" defer=""></script><script src="/showcase/_next/static/chunks/pages/_app-cafc0401ce7959b1.js" defer=""></script><script 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สำหรับสร้างรูปวาดตัวละครสาวน้อยอนิเมะ; แรงบันดาลใจจากความชื่นชอบในอนิเมะและประสบการณ์ในการทำเกมที่จำเป็นต้องออกแบบตัวละครใหม่เรื่อยๆ จึงคิดว่าน่าจะสะดวกขึ้นหากมีโมเดลที่สร้างสาวน้อยอนิเมะออกมาให้เลือกปรับใช้กับทั้งเกม, ไลท์โนเวล, รูปประกอบ ฯลฯ,\n- เลือกใช้ GAN มากกว่า Variational Autoencoder (VAE) เนื่องจากได้ภาพที่คมชัดกว่า; ด้วยข้อจำกัดทางเวลาและทรัพยากร ตั้งเป้าสร้างรูปขนาด 32², 64² หรือ 128² pixels,\n- สร้างชุดข้อมูลขึ้นมาเองด้วยมาตรฐานว่ารูปต้อง 1) ไม่มีพื้นหลัง (ขาวล้วน) 2) ลายเส้นและลักษณะตรงความต้องการ (เต็มตัว, ลายเส้นญี่ปุ่น, ตัวละครหญิง) 3) ชุดข้อมูลที่มีขนาดใหญ่ เนื่องจาก GAN ต้องใช้ชุดข้อมูลจำนวนมาก (10k ++),\n- เปรียบเทียบแหล่งข้อมูลที่จะรวบรวมมาเพื่อสร้างชุดข้อมูลหลายแห่ง เช่น Getchu ที่ปริมาณและคุณภาพดีที่สุดแต่การเชื่อมต่อไม่เสถียรพอ, Gelbooru ที่ปริมาณและคุณภาพดีเช่นกันแต่เต็มไปด้วยรูป 18+ จึงลงท้ายที่ Safebooru ซึ่งเป็น Gelbooru เวอร์ชั่นที่คัดรูป 18+ ออกแล้วโดยใช้แท้ก full_body solo, standing, 1girl, white_background เพื่อให้ได้รูปสาวน้อยอนิเมะเต็มตัวพื้นหลังสีขาว,\n- ทำความสะอาดข้อมูลด้วยการคัดรูปต่อไปนี้ออก 1) ตัวละครจิบิ (หัวโตตัวเล็ก) 2) ภาพที่มีมากกว่า 1 ตัวละคร 3) พื้นหลังสีฉูดฉาด/ท่ายืนแปลกๆ; โดยตัวละครจิบิเป็นรูปประเภทที่ไม่ต้องการที่เยอะที่สุด,\n- ทำโมเดลคัดแยกรูปที่ไม่ต้องการด้วย ResNet34 2 โมเดลคือ Chibi(~1k datasets) และ More Than 1(~0.3k datasets) ได้ผลอย่างดีเยี่ยม F1 0.96-0.98; เหลือชุดข้อมูลหลังทำความสะอาดแล้ว 12k รูป,\n- ขั้นตอนการเทรนเริ่มจากใช้ DCGAN พบว่า generator (โมเดลสร้างภาพปลอม) แทบไม่ได้เรียนรู้เลยเพราะ discriminator (โมเดลจับว่าภาพจริงหรือปลอม) เรียนรู้เร็วจนเกินไป คาดว่าปัญหาเกิดจาก vanishing gradients ของ BCE Loss ที่ใช้กับ discriminator จึงเปลี่ยนมาใช้ Wasserstein Loss และเพิ่ม gradient penalty เพื่อไม่ให้ loss ลดลงใกล้ 0 เร็วจนเกินไป,\n- จากนั้นปรับปรุงสถาปัตยกรรมโดยเปลี่ยนจาก DCGAN มาใช้ Progressive GAN ที่จะค่อยๆจับ Feature ที่ความละเอียดต่ำๆก่อน ในภาพ 4² เมื่อคุ้นชินแล้วก็จะเริ่มปรัปความละเอียดในสูงขึ้น เป็น 8² แล้วค่อยๆเพิ่มไปเรื่อยๆ จนถึง Scaling เป้าหมาย ที่ 128²,\n- เพิ่มประสิทธิผลของ generator อีกขั้นโดยการปรับใช้เทคนิคจาก StyleGAN คือ 1) Mapping Network จัดเรียง Random Noise ให้มีรูปแบบ 2) Adaptive Instance Normalization (AdaIN) เพื่อทำ style transfer; StyleGAN ได้ผลดีพอๆกับ Progressive GAN โดยใช้เวลาที่สั้นกว่า; เทรนโมเดลด้วยสถาปัตยกรรมและชุดข้อมูลนี้ เรียกว่า Model A,\n- เมื่อสถาปัตยกรรมเป็นที่พอใจแล้วกลับไปทำความสะอาดข้อมูลอีกรอบ เนื่องจากพบว่ารูปที่มี effect หรือชุดอลังการงานสร้างเกินไปจะทำให้โมเดลเรียนรู้ได้ยาก; ใช้ ResNet50 ในการคัดแยกรูปที่ต้องการและไม่ต้องการ โดยเทรนจากข้อมูลกำกับเองด้วยมือ 500 รูป, ได้ผลไม่ดีนัก (precision 0.4) ทำให้ข้อมูลถูกทำความสะอาดไปเหลือเพียงประมาณ 5 พันรูป,\n- ลองเทรน Model B บนข้อมูล 5 พันรูปนั้นแล้วพบว่าความสวยงามเป็นที่น่าพึงพอใจแม้ปริมาณรูปจะลดลงเกินครึ่ง,\n- ใช้ Fréchet inception distance (FID; ยิ่งน้อยยิ่งดี) ในการวัดผลเทียบรูปที่สร้างจาก Model A กับ Model B อย่างละ 1 หมื่นรูปกับรูปจริง พบว่า Model B ทำได้ดีกว่าเกือบเท่าตัว (data-centric มั้ยละคุณ!),\n- แม้จะมีผลลัพท์ที่ออกมาน่ากลัวอยู่บ้าง แต่โดยรวมแล้วผลลัพท์ที่ออกมา ถือว่าน่าพึงพอใจ โมเดลสามารถจับดีเทลขาได้อย่างสวยงาม ชุดที่ถูกลักษณะ ร่างกายที่สมส่วน และยังพยายามเติมหน้าเข้าไปในทุกๆโมเดล; สิ่งที่จะพัฒนาต่อหลังจากนี้คือ 1) การทดลองปรัป Noise ของโมเดล และทดสอบ Latent W เพื่อหา Style แต่ละส่วน 2) การทำให้ภาพชัดขึ้นที่ 256² 3) การหา Datasets ที่ดีขึ้นเพื่อเพิ่มคุณภาพของโมเดล 4) การ Deploy ที่ผู้ใช้สามารถปรัป Style ของรูปได้,\n- เปิดชุดข้อมูลลิขสิทธิ์การรวบรวมเป็น open source ที่: https://www.kaggle.com/datasets/hirunkulphimsiri/fullbody-anime-girls-datasets,\n- เปิด Docker Image สำหรับ deploy API เป็น open source ที่: https://gallery.ecr.aws/z1f5v2y8/ganime-fullbody/model0\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมไม่ค่อยเข้าร่วมกิจกรรมมากนัก เพราะพวกกิจกรรมที่มีมาบ่อยๆ ไม่ค่อยน่าสนใจ เช่นพวก open house หรือ แคมป์เสียเงินต่างๆ ผมชอบนั่งเรียนไปเรื่อยๆมากกว่า ดู Tutorials นั่นนี่แล้วก็ลองทำอะไรไปเรื่อยๆ ถ้าเวลาว่างๆ ผมก็จะไปตอบคำถามให้คำปรึกษาที่กลุ่มเฟสบุ๊ค/ดิสคอร์ด programming ครับ ได้ทบทวนความรู้ด้วย ได้ช่วยคนอื่นด้วย ผมว่าแบบนี้มันดีกว่าเยอะ ไม่ว่าใครจะว่ายังไง อันนี้ถือเป็นกิจกรรมที่ผมดีใจที่ได้ทำครับ  เพราะผมสนุกครับ สนุกกับการเรียนอะไรใหม่ๆ เรียนเรื่องที่ยังไม่เข้าใจ ได้แบ่งปันงานของตัวเองให้คนอื่นเอาไปพัฒนาต่อ หลักๆคือ เพราะว่ามันน่าสนุกผมเลยสมัครเข้ามา พอได้รู้อะไรมากขึ้นก็สอนคนอื่นได้มากขึ้นด้วย อีกอย่างคือผมอยากออกจากโลกแคบๆ อยากไปเจอคนใหม่ๆ ผมกังวลนความสามารถตัวเองมาตลอด ผมเลยอยากสร้างอะไรเจ๋งๆ ผมอยากพิสูจน์ตัวเอง ให้ตัวเองเห็นครับ\"","date":"8-8-22","title":"GANime-FullBody วาดรูปตัวละครอนิเมะ(สาวๆ)แบบเต็มตัว ด้วย Deep Learning","builder":"หิรัญกุล พิมพ์ศิริ 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สำหรับสร้างรูปวาดตัวละครสาวน้อยอนิเมะ; แรงบันดาลใจจากความชื่นชอบในอนิเมะและประสบการณ์ในการทำเกมที่จำเป็นต้องออกแบบตัวละครใหม่เรื่อยๆ จึงคิดว่าน่าจะสะดวกขึ้นหากมีโมเดลที่สร้างสาวน้อยอนิเมะออกมาให้เลือกปรับใช้กับทั้งเกม, ไลท์โนเวล, รูปประกอบ ฯลฯ,\n- เลือกใช้ GAN มากกว่า Variational Autoencoder (VAE) เนื่องจากได้ภาพที่คมชัดกว่า; ด้วยข้อจำกัดทางเวลาและทรัพยากร ตั้งเป้าสร้างรูปขนาด 32², 64² หรือ 128² pixels,\n- สร้างชุดข้อมูลขึ้นมาเองด้วยมาตรฐานว่ารูปต้อง 1) ไม่มีพื้นหลัง (ขาวล้วน) 2) ลายเส้นและลักษณะตรงความต้องการ (เต็มตัว, ลายเส้นญี่ปุ่น, ตัวละครหญิง) 3) ชุดข้อมูลที่มีขนาดใหญ่ เนื่องจาก GAN ต้องใช้ชุดข้อมูลจำนวนมาก (10k ++),\n- เปรียบเทียบแหล่งข้อมูลที่จะรวบรวมมาเพื่อสร้างชุดข้อมูลหลายแห่ง เช่น Getchu ที่ปริมาณและคุณภาพดีที่สุดแต่การเชื่อมต่อไม่เสถียรพอ, Gelbooru ที่ปริมาณและคุณภาพดีเช่นกันแต่เต็มไปด้วยรูป 18+ จึงลงท้ายที่ Safebooru ซึ่งเป็น Gelbooru เวอร์ชั่นที่คัดรูป 18+ ออกแล้วโดยใช้แท้ก full_body solo, standing, 1girl, white_background เพื่อให้ได้รูปสาวน้อยอนิเมะเต็มตัวพื้นหลังสีขาว,\n- ทำความสะอาดข้อมูลด้วยการคัดรูปต่อไปนี้ออก 1) ตัวละครจิบิ (หัวโตตัวเล็ก) 2) ภาพที่มีมากกว่า 1 ตัวละคร 3) พื้นหลังสีฉูดฉาด/ท่ายืนแปลกๆ; โดยตัวละครจิบิเป็นรูปประเภทที่ไม่ต้องการที่เยอะที่สุด,\n- ทำโมเดลคัดแยกรูปที่ไม่ต้องการด้วย ResNet34 2 โมเดลคือ Chibi(~1k datasets) และ More Than 1(~0.3k datasets) ได้ผลอย่างดีเยี่ยม F1 0.96-0.98; เหลือชุดข้อมูลหลังทำความสะอาดแล้ว 12k รูป,\n- ขั้นตอนการเทรนเริ่มจากใช้ DCGAN พบว่า generator (โมเดลสร้างภาพปลอม) แทบไม่ได้เรียนรู้เลยเพราะ discriminator (โมเดลจับว่าภาพจริงหรือปลอม) เรียนรู้เร็วจนเกินไป คาดว่าปัญหาเกิดจาก vanishing gradients ของ BCE Loss ที่ใช้กับ discriminator จึงเปลี่ยนมาใช้ Wasserstein Loss และเพิ่ม gradient penalty เพื่อไม่ให้ loss ลดลงใกล้ 0 เร็วจนเกินไป,\n- จากนั้นปรับปรุงสถาปัตยกรรมโดยเปลี่ยนจาก DCGAN มาใช้ Progressive GAN ที่จะค่อยๆจับ Feature ที่ความละเอียดต่ำๆก่อน ในภาพ 4² เมื่อคุ้นชินแล้วก็จะเริ่มปรัปความละเอียดในสูงขึ้น เป็น 8² แล้วค่อยๆเพิ่มไปเรื่อยๆ จนถึง Scaling เป้าหมาย ที่ 128²,\n- เพิ่มประสิทธิผลของ generator อีกขั้นโดยการปรับใช้เทคนิคจาก StyleGAN คือ 1) Mapping Network จัดเรียง Random Noise ให้มีรูปแบบ 2) Adaptive Instance Normalization (AdaIN) เพื่อทำ style transfer; StyleGAN ได้ผลดีพอๆกับ Progressive GAN โดยใช้เวลาที่สั้นกว่า; เทรนโมเดลด้วยสถาปัตยกรรมและชุดข้อมูลนี้ เรียกว่า Model A,\n- เมื่อสถาปัตยกรรมเป็นที่พอใจแล้วกลับไปทำความสะอาดข้อมูลอีกรอบ เนื่องจากพบว่ารูปที่มี effect หรือชุดอลังการงานสร้างเกินไปจะทำให้โมเดลเรียนรู้ได้ยาก; ใช้ ResNet50 ในการคัดแยกรูปที่ต้องการและไม่ต้องการ โดยเทรนจากข้อมูลกำกับเองด้วยมือ 500 รูป, ได้ผลไม่ดีนัก (precision 0.4) ทำให้ข้อมูลถูกทำความสะอาดไปเหลือเพียงประมาณ 5 พันรูป,\n- ลองเทรน Model B บนข้อมูล 5 พันรูปนั้นแล้วพบว่าความสวยงามเป็นที่น่าพึงพอใจแม้ปริมาณรูปจะลดลงเกินครึ่ง,\n- ใช้ Fréchet inception distance (FID; ยิ่งน้อยยิ่งดี) ในการวัดผลเทียบรูปที่สร้างจาก Model A กับ Model B อย่างละ 1 หมื่นรูปกับรูปจริง พบว่า Model B ทำได้ดีกว่าเกือบเท่าตัว (data-centric มั้ยละคุณ!),\n- แม้จะมีผลลัพท์ที่ออกมาน่ากลัวอยู่บ้าง แต่โดยรวมแล้วผลลัพท์ที่ออกมา ถือว่าน่าพึงพอใจ โมเดลสามารถจับดีเทลขาได้อย่างสวยงาม ชุดที่ถูกลักษณะ ร่างกายที่สมส่วน และยังพยายามเติมหน้าเข้าไปในทุกๆโมเดล; สิ่งที่จะพัฒนาต่อหลังจากนี้คือ 1) การทดลองปรัป Noise ของโมเดล และทดสอบ Latent W เพื่อหา Style แต่ละส่วน 2) การทำให้ภาพชัดขึ้นที่ 256² 3) การหา Datasets ที่ดีขึ้นเพื่อเพิ่มคุณภาพของโมเดล 4) การ Deploy ที่ผู้ใช้สามารถปรัป Style ของรูปได้,\n- เปิดชุดข้อมูลลิขสิทธิ์การรวบรวมเป็น open source ที่: https://www.kaggle.com/datasets/hirunkulphimsiri/fullbody-anime-girls-datasets,\n- เปิด Docker Image สำหรับ deploy API เป็น open source ที่: https://gallery.ecr.aws/z1f5v2y8/ganime-fullbody/model0\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมไม่ค่อยเข้าร่วมกิจกรรมมากนัก เพราะพวกกิจกรรมที่มีมาบ่อยๆ ไม่ค่อยน่าสนใจ เช่นพวก open house หรือ แคมป์เสียเงินต่างๆ ผมชอบนั่งเรียนไปเรื่อยๆมากกว่า ดู Tutorials นั่นนี่แล้วก็ลองทำอะไรไปเรื่อยๆ ถ้าเวลาว่างๆ ผมก็จะไปตอบคำถามให้คำปรึกษาที่กลุ่มเฟสบุ๊ค/ดิสคอร์ด programming ครับ ได้ทบทวนความรู้ด้วย ได้ช่วยคนอื่นด้วย ผมว่าแบบนี้มันดีกว่าเยอะ ไม่ว่าใครจะว่ายังไง อันนี้ถือเป็นกิจกรรมที่ผมดีใจที่ได้ทำครับ  เพราะผมสนุกครับ สนุกกับการเรียนอะไรใหม่ๆ เรียนเรื่องที่ยังไม่เข้าใจ ได้แบ่งปันงานของตัวเองให้คนอื่นเอาไปพัฒนาต่อ หลักๆคือ เพราะว่ามันน่าสนุกผมเลยสมัครเข้ามา พอได้รู้อะไรมากขึ้นก็สอนคนอื่นได้มากขึ้นด้วย อีกอย่างคือผมอยากออกจากโลกแคบๆ อยากไปเจอคนใหม่ๆ ผมกังวลนความสามารถตัวเองมาตลอด ผมเลยอยากสร้างอะไรเจ๋งๆ ผมอยากพิสูจน์ตัวเอง ให้ตัวเองเห็นครับ\"","date":"8-8-22","title":"GANime-FullBody วาดรูปตัวละครอนิเมะ(สาวๆ)แบบเต็มตัว ด้วย Deep Learning","builder":"หิรัญกุล พิมพ์ศิริ 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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set (1,554 รูป), validation set (170 รูป) และ test set (170 รูป),\n- ชุดข้อมูลที่ annotate เองเปิดให้ใช้เป็นสาธารณะที่ https://github.com/24GUNV/aibuilders/tree/main/object_detection/images ; แบ่งเป็นลัง (325 รูป), แก้ว (406 รูป), โลหะ (433 รูป), กระดาษ (199 รูป) และพลาสติก (191 รูป),\n- เลือกใช้สถาปัตยกรรม EfficientDet-Lite0 เพื่อ latency ที่ดีที่สุด; ได้ AP 76.6% บน test set,\n- สามารถทดลองใช้แบบ real-time ได้บน streamlit cloud; ใช้ OpenRelay เพื่อเชื่อม streamlit กับ webcam ของผู้ใช้\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"I wish to join the organization AI Builders because of my interest within the AI field. I had first been introduced to this field from a background of playing video games. I played these video games and gained an interest in what ran in the background of video games. I wanted to know how these games worked and soon began pursuing a way in which to learn how to code. I started of attempting to learn how to code in a language called LUA. It wasn\\t easy nor very successful but it opened my eyes to what was possible with the lines of code that you could write. Wanting to know more about this, I soon ventured into a course known as CS50 (https://cs50.harvard.edu/x/2021/). I learned the basics about coding such as python, c, sql, html, etc. during this course. Wanting to know more, I continued learning after finishing this course. As someone recommended to me that there was a CS50Ai course (https://cs50.harvard.edu/ai/2020/) after that I continued to expand my knowledge and finished the course. At the same time I took \"Take The World Forward Fellowship\" (https://learnwithleaders.com/taketheworldforwardfellowship/) in order to attempt to apply my knowledge to make something that could be applicable in the real world. Now I believe that the next step for me is to join \"AI Builders\" in order for my next step to apply my knowledge into something in the real world.  I wish to be a part of AI Builders because I have an interest in the AI field. I believe that AI, in the future, will be a major part of our lives. I think that by joining with this organization, I build upon and learn new concepts and lessons and apply them to the projects that I can make in the real world. I think that this organization is greater than doing it individually since we can ask the mentors from the organizations and our peers for advice on for our specific project. These mentors have experience in doing this type of stuff so it would be greatly beneficial to have them guide us through this experience. Another benefit of this organization is that they have prepared us lessons which can also guide us when creating this project. We can learn new concepts in which we can immediately use them in the real world by incorporating them into the projects that we are making.  During my time at the \"AI builders\" program, I plan to construct garbage classification machine. It should be able to the differentiate the different types of materials. An image from a camera set up inside the machine take a picture of the garbage that the user puts in. Then, based on the image, an AI will classify the type of garbage that it is. It can classify the items by the material of the item. Lastly, there will be a mechanism in the machine that can push the garbage into its specific garbage chute. This machine will help group the same types of material together, hopefully making recycling easier since the garbage is classified into different materials.\"","date":"16-7-22","title":"Garbage Detection with Tensorflow Lite","builder":"กันต์พัจน์ วิเศษสุข (กัน)","builder_info":"","thumbnail":"/images/2022/36/01.jpg","links":{"github":"https://github.com/24GUNV/aibuilders/tree/main/object_detection/images","facebook":"https://facebook.com/aibuildersx/posts/415865783915200","blog":"https://medium.com/@24progun/object-detection-using-tensorflow-lite-80da8d75c03b"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Garbage-Detection-with-Tensorflow-Lite"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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สาเหตุของความไม่ชัดคาดว่าเกิดจาก ความไวแสง (ISO; ยิ่งเพิ่มยิ่งสว่างแต่อยากทำให้เกิด noise), F-stop (เมื่อค่า F-stop ต่ำรูปจะชัดเพียงที่โฟกัสและสว่าง แต่ถ้าค่า F-stop มากก็จะทำให้ชัดทั้งภาพ แต่ภาพก็จะมืด), รวมถึงคุณภาพของกล้องและเลนส์,\n- วิธีแก้โดยไม่ใช้ ML เช่น ใช้ Adobe Lightroom ปรับค่า exposure แต่ก็จะทำให้เสียคุณภาพของรูปไป,\n- ใช้ CycleGAN ในการทำ image-to-image translation; ข้อดีคือไม่จำเป็นต้องใช้คู่รูปกลางวัน-กลางคืนของรูปเดียวกันเพราะ CycleGAN ใช้วิธี optimize ค่า cycle-consistency loss จากรูปภาพเดียวกันที่ถูกแปลงจากกลางวันเป็นกลางคืน หรือกลับกัน,\n- ใช้ PatchGAN เป็น discriminator และ generator เป็น autoencoder ที่มี residual block 9 ชั้น,\n- ทดลองรูปภาพจาก Aachen Day-Night dataset, Day-night Dataset จาก Kaggle, Mapillary Vistas Dataset, Day time and Night time road Images, Dataset Night city image; สุดท้ายใช้ภาพกลางวันจาก Mapillary Vistas Dataset และกลางคืนจาก Dataset Night city image อย่างละ 2,500 ภาพเป็น training set และอย่างละ 600 ภาพเป็น test set,\n- แปลงรูปภาพได้ค่อนข้างน่าพอใจหลังเทรนไป 55 epochs; หลัง error analysis พบภาพที่ผิด เช่น การเติมแสงไฟในรูปที่ไม่ควรเติมเมื่อแปลงรูปจากกลางวันเป็นกลางคืน คาดว่าอาจเกิดจากการที่ใน Dataset มี ภาพที่เป็นแสงไฟจากเมืองรถค่อนข้างมาก, ภาพจริงมีสะพานอยู่ แต่ภาพที่โมเดลสร้างขึ้นได้ลบสะพานให้กลายเป็นท้องฟ้า คาดว่าน่าจะเกิดจากการที่สะพานอยู่ซ้อนทับกับท้องฟ้าเลยอาจทำให้โมเดลคิดว่าสะพานเป็นส่วนหนึ่งของท้องฟ้า,\n- ใช้ FID score (Fréchet inception distance) ในการวัดคุณภาพ ในการ generate ภาพ FID score วัดได้โดยการนำรูปที่ generate หลายๆรูปกับภาพจริงจำนวนเท่ามาโยนเข้า inception v3 แล้วนำ distribution ของภาพจริงและภาพที่ generate มาเทียบกัน โดย FID ยิ่งน้อยเท่าไรก็นิ่งดีเท่านั้น; night-to-day FID = 75.68 vs day-to-night FID = 57.80 คาดว่าการเปลี่ยนภาพกลางวันเป็นกลางคืนนั้นเป็นการลดรายละเอียดของภาพซึ่งทำได้ง่ายกว่า night to day ที่เป็นการเพิ่มรายละเอียดของภาพ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เพราะโครงการ AI Builders และ อาจารย์หรือนักวิจัยหลายๆที่ได้รับเชิญเป็นหนึ่งในแรงบันดาลใจ ทำให้เริ่มต้นเส้นทางสาย AI ด้วยการศึกษาจากในอินเตอร์และเน็ตจึงทำให้มีพื้นฐาน ภาษาpython การใช้ numpy pandas ในการจัดการข้อมูล แล้วนำมาทำ Data visualization สามารถทำ web scraping ได้ รู้จักโมเดล machine learning ต่างๆ มีพื้นฐาน deep learning เล็กน้อย  เหตุผลที่ทำให้อยากเข้าร่วมโครงการเริ่มจากในปีที่แล้วได้เห็นโครงการที่มีชื่อว่า AI Builders และเกิดความสนใจเป็นอย่างมากแต่เนื่องจากปิดรับสมัคร จึงตัดสินใจติดตามกิจกรรมที่ได้ลงย้อนหลังใน facebook เป็นจุดเริ่มต้นที่จุดประกายความชอบด้าน AI จึงได้เริ่มศึกษาการเขียนโปรแกรมภาษา python และ library ต่างๆที่ใช้การจัดข้อมูลทำให้รู้สึกสนุกกับคณิตศาสตร์มากขึ้นเพราะไม่ได้ใช้คิดคำนวนเพียงในห้องเรียน แต่สามารถนำมาประยุกต์ตอบปัญหาต่างๆได้ ต่อมาค่อยศึกษาด้าน AI มากขึ้นพบว่าศาสตร์นี้มีความน่าหลงใหล ทั้งในเรื่องของการใช้แก้ปัญหา และ ในด้านแนวคิดเชิงปรัชญาในกระบวนการทำงานของ AI เมื่อโอกาศที่ดีอย่างโครงการนี้กลับมาอีกครั้งผมเลยคิดว่าต้องลงให้ได้ ถ้าได้รับคัดเลือกผมจะนำความรู้ด้านต่างๆ เช่น NLP image 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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สาเหตุของความไม่ชัดคาดว่าเกิดจาก ความไวแสง (ISO; ยิ่งเพิ่มยิ่งสว่างแต่อยากทำให้เกิด noise), F-stop (เมื่อค่า F-stop ต่ำรูปจะชัดเพียงที่โฟกัสและสว่าง แต่ถ้าค่า F-stop มากก็จะทำให้ชัดทั้งภาพ แต่ภาพก็จะมืด), รวมถึงคุณภาพของกล้องและเลนส์,\n- วิธีแก้โดยไม่ใช้ ML เช่น ใช้ Adobe Lightroom ปรับค่า exposure แต่ก็จะทำให้เสียคุณภาพของรูปไป,\n- ใช้ CycleGAN ในการทำ image-to-image translation; ข้อดีคือไม่จำเป็นต้องใช้คู่รูปกลางวัน-กลางคืนของรูปเดียวกันเพราะ CycleGAN ใช้วิธี optimize ค่า cycle-consistency loss จากรูปภาพเดียวกันที่ถูกแปลงจากกลางวันเป็นกลางคืน หรือกลับกัน,\n- ใช้ PatchGAN เป็น discriminator และ generator เป็น autoencoder ที่มี residual block 9 ชั้น,\n- ทดลองรูปภาพจาก Aachen Day-Night dataset, Day-night Dataset จาก Kaggle, Mapillary Vistas Dataset, Day time and Night time road Images, Dataset Night city image; สุดท้ายใช้ภาพกลางวันจาก Mapillary Vistas Dataset และกลางคืนจาก Dataset Night city image อย่างละ 2,500 ภาพเป็น training set และอย่างละ 600 ภาพเป็น test set,\n- แปลงรูปภาพได้ค่อนข้างน่าพอใจหลังเทรนไป 55 epochs; หลัง error analysis พบภาพที่ผิด เช่น การเติมแสงไฟในรูปที่ไม่ควรเติมเมื่อแปลงรูปจากกลางวันเป็นกลางคืน คาดว่าอาจเกิดจากการที่ใน Dataset มี ภาพที่เป็นแสงไฟจากเมืองรถค่อนข้างมาก, ภาพจริงมีสะพานอยู่ แต่ภาพที่โมเดลสร้างขึ้นได้ลบสะพานให้กลายเป็นท้องฟ้า คาดว่าน่าจะเกิดจากการที่สะพานอยู่ซ้อนทับกับท้องฟ้าเลยอาจทำให้โมเดลคิดว่าสะพานเป็นส่วนหนึ่งของท้องฟ้า,\n- ใช้ FID score (Fréchet inception distance) ในการวัดคุณภาพ ในการ generate ภาพ FID score วัดได้โดยการนำรูปที่ generate หลายๆรูปกับภาพจริงจำนวนเท่ามาโยนเข้า inception v3 แล้วนำ distribution ของภาพจริงและภาพที่ generate มาเทียบกัน โดย FID ยิ่งน้อยเท่าไรก็นิ่งดีเท่านั้น; night-to-day FID = 75.68 vs day-to-night FID = 57.80 คาดว่าการเปลี่ยนภาพกลางวันเป็นกลางคืนนั้นเป็นการลดรายละเอียดของภาพซึ่งทำได้ง่ายกว่า night to day ที่เป็นการเพิ่มรายละเอียดของภาพ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เพราะโครงการ AI Builders และ 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Lamiaceae Classification แยกพืชวงศ์กะเพรา 3 ชนิด</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->วชิรวิทย์ ไชยมาตย์ (เจ้านาย)<!-- --> • </h4><style data-emotion="css 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diff --git a/2022/Learn-Chinese-Faster-by-Using-Handwritten-Chinese-Character-Recognition-(HCCR).html b/2022/Learn-Chinese-Faster-by-Using-Handwritten-Chinese-Character-Recognition-(HCCR).html
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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diff --git a/2022/Music-Recognition.html b/2022/Music-Recognition.html
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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ทั้งจากการร้องสดและคลิปเพลง,\n- ใช้ข้อมูล 40 เพลงบน YouTube ตามยอดคนฟังเป็นความยาว 2.5 ชั่วโมง,\n- ทำความสะอาดด้วยการแยกเสียงเครื่องดนตรีจากเนื้อร้อง, ตัดเป็นคลิปเสียงคลิปละ 2-6 วินาทีด้วย Adobe Audition, คัดเนื้อร้องที่เป็นภาษาอังกฤษออก, และทำความสะอาดเครื่องหมายต่างๆ เช่น `จนผ่านวันร้ายๆ` ➜ `จนผ่านวันร้ายร้าย`; พบปัญหา เช่น เสียงร้องกลืนเข้าไปกับ BGM, เสียงคอรัสร้องหลายเนื้อร้องในเวลาเดียวกัน เป็นต้น ทำการคัดเลือกออก**ด้วยมือ**,\n- พบปัญหาเนื้อเพลงที่เป็นข้อความไม่ตรงกับเสียง; แก้ปัญหาด้วยการตัดมือแบ่งกับปืน เพื่อนในโครงการ,\n- เสียงมาจากนักร้องชาย 28 คน นักร้องหญิง 12 คน; แบ่ง train-validation-test เป็น 80:10:10,\n- มีข้อสังเกตว่าโมเดลที่ถูกเทรนบนเสียงนักร้องมืออาชีพจะสามารถถอดความเสียงมือสมัครเล่นที่ร้องเพี้ยนได้หรือเปล่า อาจจะพัฒนาเป็นโมเดลจับคนร้องเพี้ยนต่อไป,\n- ใช้ airesearch/wav2vec2-large-xlsr-53-th ที่ถูกเทรนบน Common Voice 7 เป็นโมเดลพื้นฐาน,\n- วัดผลด้วย WER (ตัดคำด้วย newmm ของ PyThaiNLP) และ CER; ทำได้ดีกว่า airesearch/wav2vec2-large-xlsr-53-th ประมาณ 3-4 เท่าบน test set\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เป็นคนที่มีความรู้ความชื่นชอบทางด้านคณิตศาสตร์เป็นอย่างมาก คณิตศาสตร์ถือเป็นวิชาที่ถนัดที่สุดสำหรับผม เป็นคนที่ถ้าได้ตั้งใจทำอะไรบางอย่างแล้วก็จะทุ่มเทให้กับสิ่งนั้น แบบ มี 100 ให้ 100 ไปเลย, มีผลงานที่เป็นผลจากความทุ่มเทอยู่บ้างเช่น การแข่งหุ่นยนตร์ รายการ wrg , สพฐ 9ล9 และกิจกรรมการเข้าร่วมกับค่าย ที่เกี่ยวกับคอมพิวเตอร์และเทคโนโลยีต่างๆ, มีเวลา พร้อมที่จะสละให้กับโครงการนี้อย่างเต็มที่, มีความสามารถเข้ากับคนอื่นได้ง่าย, และมีความสนใจในปัญญาปัญญาประดิษฐ์!  อยากเข้าเพราะ ตั้งแต่ที่ได้เห็นพัฒนาการของเทคโนโลยีตั้งแต่เด็ก จนถึงปัจุบันที่สิ่งต่างๆเติบโตขึ้นเร็วมาก มีสิ่งใหม่ๆออกมาให้เราเห็นทุกวัน ทุกอย่างทั้งน่าตื่นเต้น และน่าสนใจ จนเราเอง ก็อยากเป็นคนที่ได้ร่วมพัฒนาสิ่งเหล่านั้นแหละเติบโตไปพร้อมกับมัน แต่เนื่องจากผมไม่ได้มีประสบการณ์ในด้านนี้มาก มีแต่ความตั้งใจและความรู้ทางด้านคณิตศาสตร์ โครงการนี้จึง \"สำคัญกับผม\" ที่จะทำให้ผมได้เริ่มต้นเส้นทางนี้อย่างจริงจัง! และจะเป็นอีกหนึ่งประสบการณ์ที่จะช่วยต่อยอดการทำโครงงานจบ และการเรียนต่อมหาลัยในอาคต  อีกทั้ง เรื่องความดูแลเอาใจใส่ที่มีมาให้ตั้งแต่ยังไม่ได้ร่วมโครงการเลยด้วยซ้ำ เช่นเรื่อง Pre-course Workhop เพื่อปรับพื้นฐาน, ตารางการเรียนที่ชัดเจนจริงจัง, แบบทดสอบที่มีมาให้ม รุ่นพี่ที่ผ่านโครงการนี้มาปีที่แล้ว ก็มีแต่ผลงานเจ๋งๆ มีคุณภาพ ออกมา แบบนี้ใครจะไม่อยากเข้าร่วมโครงการนี้ครับ!! ผลงานแบบนี้ต้องมี mentor และ TA เก่งๆคอยให้คำแนะนำแน่นอน! :) ขอบคุณครับ  อยากทำ ai ที่ ช่วยเราหา \"เพลง\" เพื่อแก้ปัญหา =\u003e เวลาที่จำได้แค่ทำนองเพลง หรือถึงจำเนื้อร้องได้ แต่เนื้อร้องดันเป็นภาษาอะไรก็ไม่รู้ ทำให้เรารู้สึกหงุดหงิด คิดไม่ออกสักทีว่า เพลงที่ร้องแบบนี้มันชื่อเพลงอะไรนะ!?? มีรูปแบบการทำงานคร่าวๆ เริ่มต้นที่ รับข้อมูลเสียง(เสียงทำนอง,เสียงร้อง) \u003e ai ประมวลผล \u003e แสดงเพลงที่ประมวลผลได้ออกมาให้ผู้ใช้ ใช้ชุดข้อมูล จำพวก เนื้อเพลง และ เสียงเพลง มาจาก kaggle\"","date":"10-7-22","title":"Music Recognition","builder":"นนทพรรษ วงษ์กัณหา 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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ทั้งจากการร้องสดและคลิปเพลง,\n- ใช้ข้อมูล 40 เพลงบน YouTube ตามยอดคนฟังเป็นความยาว 2.5 ชั่วโมง,\n- ทำความสะอาดด้วยการแยกเสียงเครื่องดนตรีจากเนื้อร้อง, ตัดเป็นคลิปเสียงคลิปละ 2-6 วินาทีด้วย Adobe Audition, คัดเนื้อร้องที่เป็นภาษาอังกฤษออก, และทำความสะอาดเครื่องหมายต่างๆ เช่น `จนผ่านวันร้ายๆ` ➜ `จนผ่านวันร้ายร้าย`; พบปัญหา เช่น เสียงร้องกลืนเข้าไปกับ BGM, เสียงคอรัสร้องหลายเนื้อร้องในเวลาเดียวกัน เป็นต้น ทำการคัดเลือกออก**ด้วยมือ**,\n- พบปัญหาเนื้อเพลงที่เป็นข้อความไม่ตรงกับเสียง; แก้ปัญหาด้วยการตัดมือแบ่งกับปืน เพื่อนในโครงการ,\n- เสียงมาจากนักร้องชาย 28 คน นักร้องหญิง 12 คน; แบ่ง train-validation-test เป็น 80:10:10,\n- มีข้อสังเกตว่าโมเดลที่ถูกเทรนบนเสียงนักร้องมืออาชีพจะสามารถถอดความเสียงมือสมัครเล่นที่ร้องเพี้ยนได้หรือเปล่า อาจจะพัฒนาเป็นโมเดลจับคนร้องเพี้ยนต่อไป,\n- ใช้ airesearch/wav2vec2-large-xlsr-53-th ที่ถูกเทรนบน Common Voice 7 เป็นโมเดลพื้นฐาน,\n- วัดผลด้วย WER (ตัดคำด้วย newmm ของ PyThaiNLP) และ CER; ทำได้ดีกว่า airesearch/wav2vec2-large-xlsr-53-th ประมาณ 3-4 เท่าบน test set\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เป็นคนที่มีความรู้ความชื่นชอบทางด้านคณิตศาสตร์เป็นอย่างมาก คณิตศาสตร์ถือเป็นวิชาที่ถนัดที่สุดสำหรับผม เป็นคนที่ถ้าได้ตั้งใจทำอะไรบางอย่างแล้วก็จะทุ่มเทให้กับสิ่งนั้น แบบ มี 100 ให้ 100 ไปเลย, มีผลงานที่เป็นผลจากความทุ่มเทอยู่บ้างเช่น การแข่งหุ่นยนตร์ รายการ wrg , สพฐ 9ล9 และกิจกรรมการเข้าร่วมกับค่าย ที่เกี่ยวกับคอมพิวเตอร์และเทคโนโลยีต่างๆ, มีเวลา พร้อมที่จะสละให้กับโครงการนี้อย่างเต็มที่, มีความสามารถเข้ากับคนอื่นได้ง่าย, และมีความสนใจในปัญญาปัญญาประดิษฐ์!  อยากเข้าเพราะ ตั้งแต่ที่ได้เห็นพัฒนาการของเทคโนโลยีตั้งแต่เด็ก จนถึงปัจุบันที่สิ่งต่างๆเติบโตขึ้นเร็วมาก มีสิ่งใหม่ๆออกมาให้เราเห็นทุกวัน ทุกอย่างทั้งน่าตื่นเต้น และน่าสนใจ จนเราเอง ก็อยากเป็นคนที่ได้ร่วมพัฒนาสิ่งเหล่านั้นแหละเติบโตไปพร้อมกับมัน แต่เนื่องจากผมไม่ได้มีประสบการณ์ในด้านนี้มาก มีแต่ความตั้งใจและความรู้ทางด้านคณิตศาสตร์ โครงการนี้จึง \"สำคัญกับผม\" ที่จะทำให้ผมได้เริ่มต้นเส้นทางนี้อย่างจริงจัง! และจะเป็นอีกหนึ่งประสบการณ์ที่จะช่วยต่อยอดการทำโครงงานจบ และการเรียนต่อมหาลัยในอาคต  อีกทั้ง เรื่องความดูแลเอาใจใส่ที่มีมาให้ตั้งแต่ยังไม่ได้ร่วมโครงการเลยด้วยซ้ำ เช่นเรื่อง Pre-course Workhop เพื่อปรับพื้นฐาน, ตารางการเรียนที่ชัดเจนจริงจัง, แบบทดสอบที่มีมาให้ม รุ่นพี่ที่ผ่านโครงการนี้มาปีที่แล้ว ก็มีแต่ผลงานเจ๋งๆ มีคุณภาพ ออกมา แบบนี้ใครจะไม่อยากเข้าร่วมโครงการนี้ครับ!! ผลงานแบบนี้ต้องมี mentor และ TA เก่งๆคอยให้คำแนะนำแน่นอน! :) ขอบคุณครับ  อยากทำ ai ที่ ช่วยเราหา \"เพลง\" เพื่อแก้ปัญหา =\u003e เวลาที่จำได้แค่ทำนองเพลง หรือถึงจำเนื้อร้องได้ แต่เนื้อร้องดันเป็นภาษาอะไรก็ไม่รู้ ทำให้เรารู้สึกหงุดหงิด คิดไม่ออกสักทีว่า เพลงที่ร้องแบบนี้มันชื่อเพลงอะไรนะ!?? มีรูปแบบการทำงานคร่าวๆ เริ่มต้นที่ รับข้อมูลเสียง(เสียงทำนอง,เสียงร้อง) \u003e ai ประมวลผล \u003e แสดงเพลงที่ประมวลผลได้ออกมาให้ผู้ใช้ ใช้ชุดข้อมูล จำพวก เนื้อเพลง และ เสียงเพลง มาจาก kaggle\"","date":"10-7-22","title":"Music Recognition","builder":"นนทพรรษ วงษ์กัณหา (นน)","builder_info":"","thumbnail":"/images/2022/30/01.jpg","links":{"github":"https://github.com/Nonnyss/Ms-Wav2Vec2-Finetune","facebook":"https://facebook.com/aibuildersx/posts/411804267654685","blog":"https://medium.com/@nonthapan.wong/music-recognition-a6c9acea23e1"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Music-Recognition"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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แรงบันดาลใจจากโปรแกรมเมอร์หรือคนทำงานสาย IT ที่จบใหม่แล้วถูกกดเงินเดือนค่อนข้างมาก หรือคนที่ทำงานไปแล้วตั้งคำถามกับตัวเองว่างานที่ทำอยู่ค่าตอบแทนเหมาะสมรึเปล่า ซึ่งเป็นคำถามทั่วไปที่ตอบได้ยาก เพราะเราไม่รู้ว่าเงินเดือนของคนอื่นๆที่มีทักษะ ประสบการณ์ หรือตำแหน่งงานแบบเดียวกับเรา ได้ค่าตอบแทนเท่าไรหรือควรจะได้เท่าไร ถ้าไม่มีแหล่งข้อมูลที่มากพอหรือเวลาที่ใช้ในการหาข้อมูลเหล่านั้น ก็ไม่สามารถตอบได้อย่างมั่นใจเท่าไร,\n- พบ Thailand IT Salary Rates ซึ่งเป็นการประเมินเงินเดือนจากคนทำงาน 1,704 คนด้วย linear regression 7 ตัวแปร จึงใช้เป็น baseline ในการต่อยอด,\n- สร้างชุดข้อมูลจากการตอบแบบสอบถามสมาชิกกลุ่มหลังบ้านายอาร์ม ได้ 368 คน แบ่งเป็น train-valid-test ที่ 64:16:20,\n- ทำความสะอาดข้อมูลด้วยการรวบประเภท เช่น จังหวัด-\u003e[กรุงเทพ, อื่นๆ], ระดับการศึกษา-\u003e[ต่ำกว่าป.ตรี, ป.ตรี และสูงกว่าป.ตรี], ลบ outlier ของเงินเดือนที่สูงเกินความเป็นจริง, ลบ feature ที่ส่งสัญญาณต่อเงินเดือนน้อย เช่น อายุ, ประเภทการจ้างงาน, ภาษาโปรแกรมมิ่งที่เคยใช้, และสร้าง feature ใหม่จากข้อความอธิบายอาชีพ,\n- โมเดลใช้ 51 features จาก 6 หัวข้อใหญ่ คือ วุฒิการศึกษาสุดท้าย, จังหวัดที่ทำงานอยู่, ประสบการณ์การทำงานในองค์กร, ประสบการณ์การเขียนโปรแกรม/ฝึกฝนทั้งหมด, ขนาดองค์กรนับตามจำนวนพนักงาน, รายละเอียดตำแหน่งงานที่ทำ,\n- ใช้ AutoGluon ซึ่งเป็น open source AutoML ในการหาโมเดลที่ดีที่สุดจาก CatBoost, LightGBMLarge, LightGBMXT และ NeuralNetFastAI และทำ weighted ensemble ด้วย ridge regression,\n- ได้ผลดีกว่าโมเดล baseline คือ MAE 17798.86 (-21.83%), MSE 52472.00 (-52.78%); ตีความได้คร่าวๆว่าโมเดลประเมินคลาดเคลื่อนโดยเฉลี่ย 17,798 บาทต่อเดือน (มากที่สุดคือ 63,478 บาท น้อยที่สุด 756 บาท)\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมมีประสบการณ์ทำ Project ต่างๆ ไม่ว่าจะเป็น Web App,Desktop/Mobile App,IoT,Game Dev,Networking,Image/Signal Processing ผมจึงมีทักษะในการเขียนโปรแกรมด้วยหลายภาษารวมถึง Python ทำให้ผมสามารถเรียนรู้การสร้าง AI ได้เร็ว สามารถนำไปปรับใช้กับความรู้ที่มี และพัฒนาออกมาเป็น product ที่ใช้งานได้จริง  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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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fiction โดยทั่วไปแล้วมีมากกว่าหนึ่งแท้กจึงเลือกทำการวัดผลด้วย accuracy metric ที่ิคิดขึ้นเองคือ (% เรื่องที่มี 2 แท้กและทายถูกทั้ง 2 แท้ก) + 1/2 * (% เรื่องที่มี 1 แท้กและทายถูก) + 1/2 * (% เรื่องที่มี 2 แท้กแต่ทายถูกแค่ 1 แท้ก),\n- เขียนสคริปท์สำหรับ scrape FFNet ขึ้นมาเองเนื่องจากไม่มี API อย่างเป็นทางการโดยเลือกเฉพาะเรื่องที่เป็นภาษาอังกฤษ, K-\u003eT-rated, เรื่องที่จบแล้ว และมาจากต้นฉบับที่มีงาน fan fiction อย่างน้อย 50k เรื่อง,\n- พบว่ามีเพียง 8 genre หลักที่มีคนใช้เป็นแท้กคือ Romance, Humor, Drama, Hurt_Comfort, Adventure, Family, Angst, Friendship; แท้กมีความไม่สมดุลโดยเฉพาะ Romance ที่มีเยอะกว่าแท้กอื่นมาก,\n- เทรนโมเดลเปรียบเทียบกับ pretrained หลาย iteration เช่น bart-large-mnli, distilbert-base-uncased-mnli และ distilbart-mnli-12-1; โมเดลที่ดีที่สุดได้ค่า accuracy ตามวิธีคิดด้านบนที่ 0.437 เทียบกับ baseline ที่ 0.269\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"Although I do not have much in the way of experience in actual coding 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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เนื่องจากมะเร็งเม็ดเลือดขาวแต่ละชนิดมีการดำเนินโรคและการพยากรณ์โรคที่แตกต่างกัน,\n- ในปัจจุบันการวินิจฉัยมะเร็งเม็ดเลือดขาว จะทำการตรวจไขกระดูก (bone marrow smear or biopsy) หรือการดูจากเลือดที่เจาะจากหลอดเลือดดำ (vein)เช่น ที่แขน โดยทั้งสองวิธีนั้นจะนำเลือดมาไถดูบนสไลด์ เพื่อดูผ่านกล้องจุลทรรศน์ เรียกว่า (peripheral blood smear) เพื่อนับจำนวนเซลล์ตัวอ่อน และแยกชนิดของเซลล์ เพื่อพยากรณ์โรค ทั้งนี้ การแบ่งชนิดของมะเร็งเม็ดเลือดขาวจะมีผลต่อการเลือกวิธีการรักษาทำให้สำคัญมากๆ จำเป็นต้องอาศัยบุคลากรทางการแพทย์และผู้เชี่ยวชาญในการจำแนก จึงเป็นเหตุผลที่ดีถ้าเราจะนำ AI เข้าไป screening tools ช่วยบุคลากรทางการแพทย์ เพื่อเพิ่มประสิทธิภาพทางการรักษาได้มากยิ่งขึ้น,\n- ใช้ชุดข้อมูล microscopic image of white blood cells จาก โรงพยาบาลศิริราช โดยภายใน Dataset ประกอบด้วยรูปภาพ ตัวอ่อนของเม็ดเลือดขาวของกลุ่มคนประเภทหนึ่ง ซึ่งสามารถแบ่งเป็น 12 ชนิดด้วยกันได้แก่ Atypical lymphocyte, Band Neutrophil, Basophil, Blast, Eosinophil, Lymphocyte, Metamyelocyte, Monocyte, Myelocyte, NRC, Promyelocyte, Segmented neutrophil; ทั้งหมดจำนวน 3,376 ภาพ เป็น train set จำนวน 2700 ภาพ, validation set จำนวน 338 ภาพและ test set จำนวน 338 ภาพ,\n- ทำ data augmentation หรือ การเพิ่มจำนวน dataset เพื่อให้โมเดลได้ train ข้อมูลที่เยอะมากขึ้น จากการ rotation, cropping, horizintal flips ภาพใน dataset และ ปรับขนาดรูปภาพของเรา,\n- ทดลองใช้สถาปัตยกรรม Faster CNN (accuracy 33.53%), YOLO v5 (accuracy 51.63%) และ Swin Transformer (accuracy 56.37%),\n- จาก test set ทั้งหมด 337 ภาพสามารถทายถูก 190 ภาพและ ทายผิด 71 ภาพ และมีอีก 76 ภาพที่โมเดลของเราไม่ detect ซึ่งพอไปตรวจสอบรูปภาพเหล่านั้นพบว่าส่วนมากจะเป็นรูป ที่มีปริมาณเม็ดเลือดเกาะตัวเป็นกลุ่มทำให้ โมเดลเกิดการสับสน และจับภาพ ออกมาได้ไม่ครบถ้วนและเมื่อลองดูจากจำนวน dataset แล้วจะเห็นได้ว่า จำนวนตัวอย่างของ Promyelocyte มีจำนวนน้อยมากๆทำให้โมเดลสามารถเรียนรู้ได้น้อยและทายผิดอยู่บ้าง\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"หนูมีความแน่วแน่และสนใจด้านนี้จริงๆ หลังจากที่ได้รู้ว่า AI builders ได้เปิดรับสมัครอีกครั้ง 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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neutrophil; ทั้งหมดจำนวน 3,376 ภาพ เป็น train set จำนวน 2700 ภาพ, validation set จำนวน 338 ภาพและ test set จำนวน 338 ภาพ,\n- ทำ data augmentation หรือ การเพิ่มจำนวน dataset เพื่อให้โมเดลได้ train ข้อมูลที่เยอะมากขึ้น จากการ rotation, cropping, horizintal flips ภาพใน dataset และ ปรับขนาดรูปภาพของเรา,\n- ทดลองใช้สถาปัตยกรรม Faster CNN (accuracy 33.53%), YOLO v5 (accuracy 51.63%) และ Swin Transformer (accuracy 56.37%),\n- จาก test set ทั้งหมด 337 ภาพสามารถทายถูก 190 ภาพและ ทายผิด 71 ภาพ และมีอีก 76 ภาพที่โมเดลของเราไม่ detect ซึ่งพอไปตรวจสอบรูปภาพเหล่านั้นพบว่าส่วนมากจะเป็นรูป ที่มีปริมาณเม็ดเลือดเกาะตัวเป็นกลุ่มทำให้ โมเดลเกิดการสับสน และจับภาพ ออกมาได้ไม่ครบถ้วนและเมื่อลองดูจากจำนวน dataset แล้วจะเห็นได้ว่า จำนวนตัวอย่างของ Promyelocyte มีจำนวนน้อยมากๆทำให้โมเดลสามารถเรียนรู้ได้น้อยและทายผิดอยู่บ้าง\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"หนูมีความแน่วแน่และสนใจด้านนี้จริงๆ หลังจากที่ได้รู้ว่า AI builders ได้เปิดรับสมัครอีกครั้ง 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MiguelARD/DoorDetect-Dataset ด้วยการปรับจูนสถาปัตยกรรม Detectron2 และ Faster R-CNN R50-FPN ได้ผลไม่เป็นที่น่าพอใจ สันนิษฐานว่าเป็นเพราะคำนิยาม \"ทางเดิน\" นั้นกว้างจนเกินไป,\n- ปรับไอเดียเป็น object detection สำหรับสิ่งกีดขวาง 10 ชนิด เช่น ประตู ประตูที่เปิด ประตูตู้เย็น โต๊ะ โซฟา ฯลฯ โดยใช้ชุดข้อมูล Indoor Training Set (ITS) [RESIDE-Standard] บน Kaggle และ annotate ข้อมูลเองด้วย openvinotoolkit/CVAT; แบ่งเป็น test set ประมาณ 100 รูป,\n- ทดลองเทรน Detectron2 และ Faster R-CNN R50-FPN หลายครั้ง พร้อมทำ error analysis ว่าสิ่งกีดขวางประเภทไหนโมเดลยังจับได้ไม่ดี ได้ทำการ annotate ข้อมูลเพิ่ม,\n- สุดท้ายเปลี่ยนมาใช้สถาปัตยกรรม YOLO v5 ที่ได้ผลดีที่สุดบน test set; ยังมีสิ่งกีดขวางบางประเภท เช่น เสา ที่มีข้อมูลน้อยจนโมเดลไม่สามารถเรียนรู้ได้ดีเท่าที่ควร,\n- เปิดชุดข้อมูลเป็นสาธารณะ เข้าไปใช้งานได้ที่ https://www.kaggle.com/datasets/thepbordin/indoor-object-detection,\n- เปิด template สำหรับการ deploy YOLO v5 บน streamlit เป็น open source; เข้าไปใช้ไดที่ https://github.com/thepbordin/YOLOv5-Streamlit-Deployment\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมมีความใฝ่รู้สิ่งใหม่ๆ มีไฟในการเรียนรู้ศึกษาสิ่งใหม่ๆอย่างมาก ผมพร้อมที่จะเรียนรู้สิ่งที่โครงการนี้พร้อมที่จะมอบให้และผมจะนำไปพัฒนาให้ดีมากยิ่งขึ้น ผมยังมีประสบการณ์เข้าร่วมโครงการ Young Computer Scientist Camp #2 มหาวิทยาลัยเชียงใหม่ที่เรียนรู้เกี่ยวกับการเขียน Bot Python เบื้องต้น และมีประสบการณ์การเขียนภาษา Python มีประสบการณ์เป็นเจ้าของและผู้พัฒนาเซิร์ฟเวอร์ Minecraft และมีความเข้าใจภาษาอังกฤษได้เป็นอย่างดี ผมมั่นใจว่าถ้าผมได้เข้าร่วมโครงการนี้จะสร้างผลงานดีๆและนำไปสานต่อในอนาคตให้เกิดประโยชน์ต่อส่วนรวม  ผมมีความสนใจด้าน AI และวิทยาศาสตร์ข้อมูล และกำลังเริ่มศึกษาหาความรู้ พี่ๆของผมจึงแนะนำค่ายนี้ หลังจากที่ผมเข้าไปศึกษาดูโครงการนี้แล้วเห็นว่า โอ้โห เด็กนักเรียนระดับมัธยมก็สามารถสร้าง AI ดีๆขึ้นมาได้ ผมจึงทำการศึกษาข้อมูลเพิ่มเติมและตั้งเป้าหมายให้ได้เข้าร่วมโครงการนี้ และในที่สุดผมจะนำความรู้ที่ได้จากโครงการไปพัฒนาปัญญาประดิษฐ์ที่ใช้งานได้จริง และมีประโยชน์ต่อผู้อื่น นั่นจะเป็นหนึ่งในความภาคภูมิใจของผม  ผมอยากทำโครงงานแก้ไขปัญหาให้กับผู้พิการทางสายตา ที่เดินทาง Indoor ได้ลำบาก โดยใช้ Image Processing ร่วมกับโมเดล Text to Speech ของผู้ศึกษาโครงการ AI Builders รุ่นแรกโดยภาพที่ได้จากกล้องที่ติดบนหมวกของผู้พิการทางสายตานำไปประมวลผลกับโมเดลที่เทรนโดย https://www.kaggle.com/datasets/hamzafar/look4me จะได้ทิศทางการเดินที่เป็นไปได้แล้วตอบกลับด้วยเสียง โดยใช้ Thai TTS Tacotron (สามารถเดินตรงไป เลี้ยวซ้ายและเลี้ยวขวาได้) หรืออาจจะรับข้อมูลจากไม้เท้าของผู้พิการทางสายตาว่าชี้ไปทิศทางไหน แล้วให้ตอบกลับว่าทิศทางนั้นเป็นไปได้หรือไม่ และในอนาคตอาจนำไปสานต่อกับการเดิน Outdoor ของผู้พิการทางสายตาบอกถึง ทางม้าลาย ทางเดินเท้าที่เป็นไปได้ หรือยานพาหนะต่างๆ ให้มีความปลอดภัยมากขึ้น\"","date":"3-8-22","title":"Obstacle Detection for Blind people ช่วยเหลือผู้พิการทางสายตาด้วย Deep Learning","builder":"เทพบดินทร์ ใจอินสม 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MiguelARD/DoorDetect-Dataset ด้วยการปรับจูนสถาปัตยกรรม Detectron2 และ Faster R-CNN R50-FPN ได้ผลไม่เป็นที่น่าพอใจ สันนิษฐานว่าเป็นเพราะคำนิยาม \"ทางเดิน\" นั้นกว้างจนเกินไป,\n- ปรับไอเดียเป็น object detection สำหรับสิ่งกีดขวาง 10 ชนิด เช่น ประตู ประตูที่เปิด ประตูตู้เย็น โต๊ะ โซฟา ฯลฯ โดยใช้ชุดข้อมูล Indoor Training Set (ITS) [RESIDE-Standard] บน Kaggle และ annotate ข้อมูลเองด้วย openvinotoolkit/CVAT; แบ่งเป็น test set ประมาณ 100 รูป,\n- ทดลองเทรน Detectron2 และ Faster R-CNN R50-FPN หลายครั้ง พร้อมทำ error analysis ว่าสิ่งกีดขวางประเภทไหนโมเดลยังจับได้ไม่ดี ได้ทำการ annotate ข้อมูลเพิ่ม,\n- สุดท้ายเปลี่ยนมาใช้สถาปัตยกรรม YOLO v5 ที่ได้ผลดีที่สุดบน test set; ยังมีสิ่งกีดขวางบางประเภท เช่น เสา ที่มีข้อมูลน้อยจนโมเดลไม่สามารถเรียนรู้ได้ดีเท่าที่ควร,\n- เปิดชุดข้อมูลเป็นสาธารณะ เข้าไปใช้งานได้ที่ https://www.kaggle.com/datasets/thepbordin/indoor-object-detection,\n- เปิด template สำหรับการ deploy YOLO v5 บน streamlit เป็น open source; เข้าไปใช้ไดที่ https://github.com/thepbordin/YOLOv5-Streamlit-Deployment\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผมมีความใฝ่รู้สิ่งใหม่ๆ มีไฟในการเรียนรู้ศึกษาสิ่งใหม่ๆอย่างมาก ผมพร้อมที่จะเรียนรู้สิ่งที่โครงการนี้พร้อมที่จะมอบให้และผมจะนำไปพัฒนาให้ดีมากยิ่งขึ้น ผมยังมีประสบการณ์เข้าร่วมโครงการ Young Computer Scientist Camp #2 มหาวิทยาลัยเชียงใหม่ที่เรียนรู้เกี่ยวกับการเขียน Bot Python เบื้องต้น และมีประสบการณ์การเขียนภาษา Python มีประสบการณ์เป็นเจ้าของและผู้พัฒนาเซิร์ฟเวอร์ Minecraft และมีความเข้าใจภาษาอังกฤษได้เป็นอย่างดี ผมมั่นใจว่าถ้าผมได้เข้าร่วมโครงการนี้จะสร้างผลงานดีๆและนำไปสานต่อในอนาคตให้เกิดประโยชน์ต่อส่วนรวม  ผมมีความสนใจด้าน AI และวิทยาศาสตร์ข้อมูล และกำลังเริ่มศึกษาหาความรู้ พี่ๆของผมจึงแนะนำค่ายนี้ หลังจากที่ผมเข้าไปศึกษาดูโครงการนี้แล้วเห็นว่า โอ้โห เด็กนักเรียนระดับมัธยมก็สามารถสร้าง AI ดีๆขึ้นมาได้ ผมจึงทำการศึกษาข้อมูลเพิ่มเติมและตั้งเป้าหมายให้ได้เข้าร่วมโครงการนี้ 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Plant Disease Classification</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->รัชชานนท์ มุขแก้ว (นนท์)<!-- --> • </h4><style data-emotion="css 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diff --git a/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide.html b/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide.html
index 268f043..298c500 100644
--- a/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide.html
+++ b/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide.html
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Sick Pig Classifier</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->ภวัต ลีชาแสน (บีม)<!-- --> • </h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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เลยถือโอกาสมาลองฝึก “Perfect Pitch” กับ Model ดู,\n- ชุดข้อมูลจากไฟล์เสียง MIDI ที่สร้างขึ้น ประกอบไปด้วยเสียงโน๊ตตั้งแต่ C0-B9 ที่เล่นโดยเครื่องดนตรีต่างชนิดกัน มีไฟล์เสียงทั้งสิ้น 26,643 ไฟล์,\n- จัดการข้อมูลโดย 1) resample เสียงให้มีความละเอียดที่ 16000 Hz 2) mix down ในกรณีที่ไฟล์บางไฟล์มีการแยก channel ซ้าย/ขวา เราจะรวมเสียงให้มาอยู่ใน mono channel 3) เปลี่ยนเป็น mel spectrogram ซึ่งเป็น short-time fourier transform ที่เน้นแค่คลื่นเสียงต่ำอันเสียงออกมาเป็นค่าที่ใกล้เคียงกับค่าที่มนุษย์ได้ยิน; ที่จริงเรายังสามารถ take log ลงไปเพื่อให้ range ของข้อมูลไม่กว้างและกระโดดมาถึง 20,000 แต่เนื่องจากการ predict note เราดูแค่ frequency เสียงที่โดดขึ้นมา จึงไม่ได้มีผลต่อการทำนายมากนัก กลับกัน หากเป็น speech ก็จะทำให้เกิดปัญหาตามมาได้,\n- โมเดลรับข้อมูล tensor ของ data ที่มี size เป็น (128,50) แล้วส่งเข้าโมเดลก่อนจะ predict ค่ามาเป็น index ของ classmap ตั้งแต่ 0–12 (classmap=[“C”,”C#”,”D”,”D#”,”E”,”F”,”F#”,”G”,”G#”,”A”,”A#”,”B”]),\n- เทรน 1D CNN 3 layers (ขนาด channel 128 -\u003e 256 -\u003e 512) ด้วย cross-entropy loss; ใช้ BatchNorm1D มา normalization ข้อมูลก่อนออกจาก layer ก่อนจะใช้ Activation ReLU เพื่อจะกำจัดค่าที่น้อยกว่า 0 ออกเป็นตอนสุดท้ายเพราะความถี่เสียงมีค่าติดลบไม่ได้,\n- ได้ accuracy 96.48% หลังเทรนไป 20 epochs,\n- นอกจากนี้ยังได้ทำอีกโครงการสำหรับแยกแยะโน้ตที่เรียงกัน 1,500 time steps จากชุดข้อมูล MusicNet (https://zenodo.org/record/5120004#.YrHWQLlBxQI) อีกด้วย; ทดลองสถาปัตยกรรมากมายได้แก่ Conv1d -\u003e Conv1d -\u003e Linear, Conv1d -\u003e RELU -\u003e Linear(บนแกน time) -\u003e LSTM(บนแกน feature), Convo1d -\u003e LSTM(time) -\u003e Linear(time) -\u003e LSTM(feature), Conv1d(kernel = 6) -\u003e ReLU -\u003e Conv1d(kernel = 8) -\u003e LSTM แต่ปัญหาการทายโน้ตหลายตัวพร้อมกันยังยากกว่าทายตัวเดียวมาก (อ่านต่อได้ที่ https://neennera.medium.com/%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%9E%E0%B8%B1%E0%B8%92%E0%B8%99%E0%B8%B2-model-%E0%B9%81%E0%B8%A2%E0%B8%81%E0%B9%82%E0%B8%99%E0%B9%8A%E0%B8%95%E0%B8%94%E0%B8%99%E0%B8%95%E0%B8%A3%E0%B8%B5%E0%B9%83%E0%B8%99%E0%B9%80%E0%B8%9E%E0%B8%A5%E0%B8%87-%E0%B9%82%E0%B8%94%E0%B8%A2-pytorch-b239dc0e956c)\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เราให้นิยามตัวเองว่าเป็นคนที่มีความพยายามต่องานที่ทำอยู่เสมอ จึงมั่นใจได้ว่าเราจะทำโปรเจคนี้อย่างเต็มความสามารถ เรามีความรู้ในการเขียนโปรแกรมภาษา python มาจากการศึกษาด้วยตนเองเพื่อทำ project ในโรงเรียนและมีความกระตือรือร้นที่จะเรียนรู้อีก เรายังได้ทำการศึกษาการเขียนโปรแกรมมาหลากหลายผ่านการเข้าค่ายโอลิมปิกวิชาการคอมพิวเตอร์ค่าย 2 ที่ทำให้เราได้เข้าใจ algorithm ที่หลากหลาย เราได้ร่วมพัฒนาโครงการเครื่องให้อาหารแมวที่ควบคุมบน Web Application และทำงานร่วมกับระบบ IoT โดยตลอดเวลาที่ทำงานเหล่านั้นเราศึกษาบนเว็บต่างประเทศจึงสามารถอ่าน, แปล, และทำความเข้าใจบทความหรือ paper ภาษาอังกฤษได้ดีมาก เรามีแรงบันดาลใจในการสร้าง AI แก้ปัญหาในชีวิตประจำวัน แม้จะเป็นปัญหาเฉพาะกลุ่มแต่ก็สามารถสร้างความแปลกใหม่ได้ เราคาดหวังอย่างยิ่งว่าจะได้รับโอกาสในการทำความฝันนั้นให้เป็นจริง  ปฏิเสธไม่ได้ว่า Artificial Intelligence ได้เข้ามาบทบาทอย่างมากในปัจจุบัน ทั้งช่วยย่นการทำงานของมนุษย์ ช่วยจำแนกหรือวิเคราะห์ข้อมูลที่ซับซ้อน แนะนำ content ที่เกี่ยวข้อง หรือแม้แต่ช่วยตัดสินใจ แต่ก็ใช่ว่า AI จะสามารถทำได้ทุกอย่างหรือแม้แต่การทำงานออกมาได้ perfect 100% ก็เป็นไปได้ยากหากขาด dataset , การจัดการข้อมูลที่ดี หรือ วิธีการ train model ที่เหมาะสม ซึ่งสิ่งนี้จำเป็นต้องศึกษาเพิ่มเติมกว่าความรู้ในม.ปลายไปมาก และจำเป็นต้องพึ่งพาผู้ที่มีประสบการณ์มากกว่า  เราสนใจโครงการ AI Builder ตั้งแต่ปีที่แล้ว แม้จะไม่ผ่านรอบคัดเลือกตัวจริงแต่ก็ได้ศึกษาเนื้อหาไปบ้างในแบบของนักเรียน sit-in หลังจากเห็นโครงงานของเพื่อนหลายคนก็ทำให้เรามีไฟที่อยากจะมาลองสมัครรอบของปีนี้อีก! AI Builder มีเนื้อหาที่เข้มข้นและสิ่งที่สำคัญคือการมี mentor ที่เชี่ยวชาญ และกลุ่มเพื่อนเข้ามาช่วยให้คำปรึกษา เราจึงคิดว่าหากได้เข้าร่วมโครงการนี้แล้ว คงจะได้พัฒนาฝีมือตัวเองให้ดีขึ้นและเข้าใจถึงการพัฒนาโปรเจค AI อย่างเต็มรูปแบบจนอาจสามารถตกตะกอนความรู้และถ่ายทอดให้ผู้อื่นได้ในภายหลัง\"","date":"14-8-22","title":"Single Note Music Classification","builder":"ณภัทร เสรีรักษ์ (นีร)","builder_info":"","thumbnail":"/images/2022/65/01.jpg","links":{"github":"https://github.com/neennera/AI_single-music-note-classification","facebook":"https://facebook.com/aibuildersx/posts/452054363629675","blog":"https://neennera.medium.com/single-note-music-classification-by-convolutional-neural-networks-5f72434d139a"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Single-Note-Music-Classification"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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เลยถือโอกาสมาลองฝึก “Perfect Pitch” กับ Model ดู,\n- ชุดข้อมูลจากไฟล์เสียง MIDI ที่สร้างขึ้น ประกอบไปด้วยเสียงโน๊ตตั้งแต่ C0-B9 ที่เล่นโดยเครื่องดนตรีต่างชนิดกัน มีไฟล์เสียงทั้งสิ้น 26,643 ไฟล์,\n- จัดการข้อมูลโดย 1) resample เสียงให้มีความละเอียดที่ 16000 Hz 2) mix down ในกรณีที่ไฟล์บางไฟล์มีการแยก channel ซ้าย/ขวา เราจะรวมเสียงให้มาอยู่ใน mono channel 3) เปลี่ยนเป็น mel spectrogram ซึ่งเป็น short-time fourier transform ที่เน้นแค่คลื่นเสียงต่ำอันเสียงออกมาเป็นค่าที่ใกล้เคียงกับค่าที่มนุษย์ได้ยิน; ที่จริงเรายังสามารถ take log ลงไปเพื่อให้ range ของข้อมูลไม่กว้างและกระโดดมาถึง 20,000 แต่เนื่องจากการ predict note เราดูแค่ frequency เสียงที่โดดขึ้นมา จึงไม่ได้มีผลต่อการทำนายมากนัก กลับกัน หากเป็น speech ก็จะทำให้เกิดปัญหาตามมาได้,\n- โมเดลรับข้อมูล tensor ของ data ที่มี size เป็น (128,50) แล้วส่งเข้าโมเดลก่อนจะ predict ค่ามาเป็น index ของ classmap ตั้งแต่ 0–12 (classmap=[“C”,”C#”,”D”,”D#”,”E”,”F”,”F#”,”G”,”G#”,”A”,”A#”,”B”]),\n- เทรน 1D CNN 3 layers (ขนาด channel 128 -\u003e 256 -\u003e 512) ด้วย cross-entropy loss; ใช้ BatchNorm1D มา normalization ข้อมูลก่อนออกจาก layer ก่อนจะใช้ Activation ReLU เพื่อจะกำจัดค่าที่น้อยกว่า 0 ออกเป็นตอนสุดท้ายเพราะความถี่เสียงมีค่าติดลบไม่ได้,\n- ได้ accuracy 96.48% หลังเทรนไป 20 epochs,\n- นอกจากนี้ยังได้ทำอีกโครงการสำหรับแยกแยะโน้ตที่เรียงกัน 1,500 time steps จากชุดข้อมูล MusicNet (https://zenodo.org/record/5120004#.YrHWQLlBxQI) อีกด้วย; ทดลองสถาปัตยกรรมากมายได้แก่ Conv1d -\u003e Conv1d -\u003e Linear, Conv1d -\u003e RELU -\u003e Linear(บนแกน time) -\u003e LSTM(บนแกน feature), Convo1d -\u003e LSTM(time) -\u003e Linear(time) -\u003e LSTM(feature), Conv1d(kernel = 6) -\u003e ReLU -\u003e Conv1d(kernel = 8) -\u003e LSTM แต่ปัญหาการทายโน้ตหลายตัวพร้อมกันยังยากกว่าทายตัวเดียวมาก (อ่านต่อได้ที่ https://neennera.medium.com/%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%9E%E0%B8%B1%E0%B8%92%E0%B8%99%E0%B8%B2-model-%E0%B9%81%E0%B8%A2%E0%B8%81%E0%B9%82%E0%B8%99%E0%B9%8A%E0%B8%95%E0%B8%94%E0%B8%99%E0%B8%95%E0%B8%A3%E0%B8%B5%E0%B9%83%E0%B8%99%E0%B9%80%E0%B8%9E%E0%B8%A5%E0%B8%87-%E0%B9%82%E0%B8%94%E0%B8%A2-pytorch-b239dc0e956c)\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"เราให้นิยามตัวเองว่าเป็นคนที่มีความพยายามต่องานที่ทำอยู่เสมอ จึงมั่นใจได้ว่าเราจะทำโปรเจคนี้อย่างเต็มความสามารถ เรามีความรู้ในการเขียนโปรแกรมภาษา python มาจากการศึกษาด้วยตนเองเพื่อทำ project ในโรงเรียนและมีความกระตือรือร้นที่จะเรียนรู้อีก เรายังได้ทำการศึกษาการเขียนโปรแกรมมาหลากหลายผ่านการเข้าค่ายโอลิมปิกวิชาการคอมพิวเตอร์ค่าย 2 ที่ทำให้เราได้เข้าใจ algorithm ที่หลากหลาย เราได้ร่วมพัฒนาโครงการเครื่องให้อาหารแมวที่ควบคุมบน Web Application และทำงานร่วมกับระบบ IoT โดยตลอดเวลาที่ทำงานเหล่านั้นเราศึกษาบนเว็บต่างประเทศจึงสามารถอ่าน, แปล, และทำความเข้าใจบทความหรือ paper ภาษาอังกฤษได้ดีมาก เรามีแรงบันดาลใจในการสร้าง AI แก้ปัญหาในชีวิตประจำวัน แม้จะเป็นปัญหาเฉพาะกลุ่มแต่ก็สามารถสร้างความแปลกใหม่ได้ เราคาดหวังอย่างยิ่งว่าจะได้รับโอกาสในการทำความฝันนั้นให้เป็นจริง  ปฏิเสธไม่ได้ว่า Artificial Intelligence ได้เข้ามาบทบาทอย่างมากในปัจจุบัน ทั้งช่วยย่นการทำงานของมนุษย์ ช่วยจำแนกหรือวิเคราะห์ข้อมูลที่ซับซ้อน แนะนำ content ที่เกี่ยวข้อง หรือแม้แต่ช่วยตัดสินใจ แต่ก็ใช่ว่า AI จะสามารถทำได้ทุกอย่างหรือแม้แต่การทำงานออกมาได้ perfect 100% ก็เป็นไปได้ยากหากขาด dataset , การจัดการข้อมูลที่ดี หรือ วิธีการ train model ที่เหมาะสม ซึ่งสิ่งนี้จำเป็นต้องศึกษาเพิ่มเติมกว่าความรู้ในม.ปลายไปมาก และจำเป็นต้องพึ่งพาผู้ที่มีประสบการณ์มากกว่า  เราสนใจโครงการ AI Builder ตั้งแต่ปีที่แล้ว แม้จะไม่ผ่านรอบคัดเลือกตัวจริงแต่ก็ได้ศึกษาเนื้อหาไปบ้างในแบบของนักเรียน sit-in หลังจากเห็นโครงงานของเพื่อนหลายคนก็ทำให้เรามีไฟที่อยากจะมาลองสมัครรอบของปีนี้อีก! AI Builder มีเนื้อหาที่เข้มข้นและสิ่งที่สำคัญคือการมี mentor ที่เชี่ยวชาญ และกลุ่มเพื่อนเข้ามาช่วยให้คำปรึกษา เราจึงคิดว่าหากได้เข้าร่วมโครงการนี้แล้ว คงจะได้พัฒนาฝีมือตัวเองให้ดีขึ้นและเข้าใจถึงการพัฒนาโปรเจค AI อย่างเต็มรูปแบบจนอาจสามารถตกตะกอนความรู้และถ่ายทอดให้ผู้อื่นได้ในภายหลัง\"","date":"14-8-22","title":"Single Note Music Classification","builder":"ณภัทร เสรีรักษ์ (นีร)","builder_info":"","thumbnail":"/images/2022/65/01.jpg","links":{"github":"https://github.com/neennera/AI_single-music-note-classification","facebook":"https://facebook.com/aibuildersx/posts/452054363629675","blog":"https://neennera.medium.com/single-note-music-classification-by-convolutional-neural-networks-5f72434d139a"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Single-Note-Music-Classification"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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ขนาดเท่ากันจึงสามารถนำทั้ง Text embedding และ Image embedding มาเปรียบเทียบความเหมือนความต่างได้โดยใช้วิธีการทางคณิตศาตร์ต่าง ๆ CLIP จะประกอบไปด้วยโมเดลหลัก 2 ส่วนคือ Text encoder และ Image encoder,\n- VQGAN เป็นโมเดลประเภท Generative โดยจะประกอบไปด้วย Generator และ Discriminator โมเดลสองตัวนี้จะแข่งกันและพัฒนาตัวเองไปพร้อม ๆ กันจนในที่สุด Discriminator ไม่สามารถเอาชนะ Generator ได้ เราจึงจะนำ Generator ไปสร้างภาพต่อ นอกจากนี้ก่อนที่ทั้งสองโมเดลนี้จะแข่งกัน Generator จะได้เรียนรู้โครงสร้างของภาพที่ตัวเองจะสร้างไว้ก่อน เปรียบเสมือนมีสมุดเปล่าที่เอาไว้จดวิธีการสร้างสิ่งต่าง ๆ ลงไป,\n- เนื่องจากการจะสร้างรูปจาก VQGAN นั้นต้องมี Random input (กลุ่มตัวเลขแบบสุ่ม) ส่งเข้าไปให้ Generator จึงจะสร้างเป็นรูปต่าง ๆ ได้และแน่นอนว่าเราไม่สามารถรู้ได้ว่าการสุ่มแบบไหนจะให้รูปที่เราต้องการได้ จึงต้องใช้ CLIP คอยกำกับและค่อย ๆ เปลี่ยน Random input เหล่านี้ให้เป็นรูปที่เราต้องการ,\n- วิธี #1: เริ่มจากการเทรน CLIP ขึ้นมาเองใช้ข้อมูลเริ่มจาก flicker8k (8,000 รูป) ไปจนถึง flicker30k (30,000 รูป) แปลข้อมูล caption จากภาษาอังกฤษไปไทยด้วย PyThaiNLP; ใช้ resnet-50 เป็น image encoder และ WangchanBERTa เป็น text encoder (ThCLIP),\n- วิธีแรกยังไม่ได้ผลเป็นที่น่าพึงพอใจด้วยปัจจัยขนาดชุดข้อมูลและเวลาในการเทรน จึงทดลองวิธี knowledge distillation สำหรับ CLIP แทน,\n- วิธี #2: เทรนใหม่โดยการสอนให้ ThCLIP สร้าง text embeddings ให้คล้ายกับ OpenAI CLIP มากที่สุดตาม mean-squared error loss; ใช้ปริมาณข้อมูลน้อยกว่าและได้ผลดีกว่ามาก,\n- เทรนตามวิธี #2 ด้วยข้อมูล 2 ล้านรูป สุ่มจาก GCC, MSCOCO เหมือนของ SwedishCLIP,\n- จากการ \"ทดลอง ทดลอง ทดลอง\" พบว่า transform ภาพโดยสุ่มเพิ่มระดับ sharpness ให้กับภาพทำให้กราฟ Loss converge เร็วขึ้น, iteration ที่เหมาะที่สุดอยู่ระหว่าง 200–300 รอบ, รวมถึง:,\n- ใช้ negative prompt เพื่อพัฒนาคุณภาพรูปภาพได้ เช่น เมื่อสร้างภาพ \"เครื่องบิน\" ให้ \"ภาพเบลอ\" เป็น negative prompt (ใส่เข้าไปใน loss function) จะทำให้ได้ภาพเครื่องบินที่ชัดขึ้น,\n- ใช้ aesthetic-predictor จาก pretrained model ที่ประเมิน \"ความสวย\" ของรูป และให้ความสวยเป็นส่วนหนึ่งของ loss function; ทำให้รูปที่ออกมาสวยขึ้น,\n- ทดสอบประสิทธิภาพโมเดลด้วยแบบสอบถามจาก 27 คน พบว่า VGQAN-ThCLIP (โมเดลของเรา) ทำได้ดีกว่า VQGAN-CLIP (pretrained จาก OpenAI) เมื่อรูปภาพถูกสร้างจากข้อความสั้นทั้งด้านความสอดคล้องและความหลากหลาย แต่ยิ่งข้อความยาวทำได้ดีกว่าในด้านความสอดคล้องแต่ด้อยกว่าในด้านความหลากหลาย,\n- โมเดลสามารถทำ prompting ได้เหมือน text-to-image ชั้นนำทั่วไป เช่น \"คฤหาสน์\", \"คฤหาสน์ แฟนตาซี\", \"คฤหาสน์ แฮรี่พอตเตอร์\" ฯลฯ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผู้เขียนมีความสนใจทางด้าน machine learning เป็นอย่างมากและยังมีความมุ่งมั่นที่จะทำให้สำเร็จ ปัจจุบัน machine learning \u0026 AI มีบทบาทกับเราแทบทุกด้าน แต่การจะทำให้ AI ใช้งานได้ในแต่ละด้านนั้นแตกต่างกันอย่างสิ้นเชิง ผู้เขียนจึงอยากเก็บเกี่ยวประสบการณ์ตั้งแต่การสร้างไปจนถึงการนำไปใช้ของ Machine learning \u0026 AI ในแต่ละด้านเพื่อขยายขอบเขตไอเดียของตัวเองและเมื่อไอเดียที่เข้าท่ามาถึง ผู้เขียนก็สามารถลงมือทำได้เลย โดยรู้ว่าด้านที่จะทำนั้นต้องใช้ model ประมาณนี้ รู้แหล่งชุดข้อมูลและรู้คีย์เวิร์ดที่จะศึกษาเพิ่มเติม นอกจากนั้นการเข้าโครงการนี้จะทำให้เราได้เจอกับเมนเทอร์และเพื่อนร่วมโครงการที่มีความชอบ เหมือนๆ กัน เมื่อเค้ามีความถนัดในด้าน machine learing ที่เราจะทำเราก็สามารถขอคำแนะนำจากเค้าได้และในทางกลับกันเราก็สามารถให้คำแนะนำในด้านที่เราถนัดแก่เพื่อนร่วมโครงการได้เช่นกัน เป้าหมายของผู้เขียนคือการสร้างนวัตกรรมหรือสิ่งประดิษฐ์ที่ทุกคนสามารถใช้ได้อย่างแพร่หลายและเกิดประโยชน์จากการใช้งานนั้น ซึ่งปัจจุบันผู้เขียนอยากศึกษาเพิ่มเติมทางด้าน Machine learning \u0026 AI อยากลองศึกษาศาสตร์แขนงใหม่ๆของ machine learing อาทิเข่น NLP, time series, GAN และอยากศึกษาวิธีการนำไปปรับใช้กับปัญหาในชีวิตจริง  อยากทำการสร้างรูปสังเคราะห์จากข้อความภาษาไทย (text to image genarator) เพื่อจำลองการออกแบบผลิตภัณฑ์เบื้องต้นจากไอเดียแล้วนำไปประเมิณว่าสามารถนำไปต่อยอดได้มากเพียงใดหรือเพื่อค้นพบไอเดียใหม่จากรูปที่สังเคราะห์ขึ้นมา เช่น อยากออกแบบดีไซน์เก้าอี้จึงพิมพ์ไปว่าเก้าอี้ทรงทุเรียน ตัวโมเดลอาจจะให้ผลลัพธ์เป็นเก้าอี้ที่มีหนามทุเรียนเป็นขาหรือเก้าอี้ที่ใช้หนามมนเป็นที่นั่ง และอื่นๆที่ผู้เขียนคาดไม่ถึง ชุดข้อมูลรูป ใช้จาก COCO โดยส่วนมากจะเป็นรูปสิ่งของต่างๆ, ชุดข้อมูลคำ ใช้คำที่ผ่านการ embedded มาแล้วโดยใช้ thai2vec ด้วย PyThaiNLP, นอกจากนี้ถ้าเปลี่ยนชุดข้อมูลใหม่โดยใช้รูปหน้าคนแล้วเทรนให้โมเดลสร้างหน้าคนจากคำบอกเล่าของพยานก็จะสามารถสร้างรูปคนร้ายเพื่อใช้ในการตามหาตัวหรือทำรูปติดประกาศจับ การทำแบบนี้จะสามารถลดระยะเวลาการสเก็ตช์ภาพขั้นต้นและสามารถโฟกัสกับการปรับแต่งขั้นสุดท้ายให้ภาพตรงกับคนร้ายที่พยานเห็นมากที่สุด ก็เป็นอีกโครงงานหนึ่งที่น่าทำเช่นกัน\"","date":"12-7-22","title":"Text-to-image synthesis with VQGAN-ThCLIP","builder":"ภูริช ศิริทิพย์ (มาร์ค)","builder_info":"","thumbnail":"/images/2022/32/01.jpg","links":{"github":"https://colab.research.google.com/github/vikimark/VQGAN-ThCLIP/blob/master/Streamlit_VQGANxThaiCLIP.ipynb","facebook":"https://facebook.com/aibuildersx/posts/413224897512622","blog":"https://medium.com/@phuritsiritip/%E0%B9%82%E0%B8%84%E0%B8%A3%E0%B8%87%E0%B8%81%E0%B8%B2%E0%B8%A3-ai-builders-%E0%B8%81%E0%B8%B1%E0%B8%9A-ai-%E0%B8%AA%E0%B8%A3%E0%B9%89%E0%B8%B2%E0%B8%87%E0%B8%A0%E0%B8%B2%E0%B8%9E%E0%B8%88%E0%B8%B2%E0%B8%81%E0%B8%82%E0%B9%89%E0%B8%AD%E0%B8%84%E0%B8%A7%E0%B8%B2%E0%B8%A1%E0%B8%AA%E0%B8%A3%E0%B9%89%E0%B8%B2%E0%B8%87%E0%B9%82%E0%B8%94%E0%B8%A2%E0%B9%80%E0%B8%94%E0%B9%87%E0%B8%81%E0%B8%A1%E0%B8%B1%E0%B8%98%E0%B8%A2%E0%B8%A1%E0%B8%9B%E0%B8%A5%E0%B8%B2%E0%B8%A2-%E0%B8%97%E0%B8%B5%E0%B9%88%E0%B9%80%E0%B8%81%E0%B8%B7%E0%B8%AD%E0%B8%9A%E0%B8%88%E0%B8%B0%E0%B8%82%E0%B8%B6%E0%B9%89%E0%B8%99%E0%B8%9B%E0%B8%B5-1-ed5878c7a72c"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Text-to-image-synthesis-with-VQGAN-ThCLIP"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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ขนาดเท่ากันจึงสามารถนำทั้ง Text embedding และ Image embedding มาเปรียบเทียบความเหมือนความต่างได้โดยใช้วิธีการทางคณิตศาตร์ต่าง ๆ CLIP จะประกอบไปด้วยโมเดลหลัก 2 ส่วนคือ Text encoder และ Image encoder,\n- VQGAN เป็นโมเดลประเภท Generative โดยจะประกอบไปด้วย Generator และ Discriminator โมเดลสองตัวนี้จะแข่งกันและพัฒนาตัวเองไปพร้อม ๆ กันจนในที่สุด Discriminator ไม่สามารถเอาชนะ Generator ได้ เราจึงจะนำ Generator ไปสร้างภาพต่อ นอกจากนี้ก่อนที่ทั้งสองโมเดลนี้จะแข่งกัน Generator จะได้เรียนรู้โครงสร้างของภาพที่ตัวเองจะสร้างไว้ก่อน เปรียบเสมือนมีสมุดเปล่าที่เอาไว้จดวิธีการสร้างสิ่งต่าง ๆ ลงไป,\n- เนื่องจากการจะสร้างรูปจาก VQGAN นั้นต้องมี Random input (กลุ่มตัวเลขแบบสุ่ม) ส่งเข้าไปให้ Generator จึงจะสร้างเป็นรูปต่าง ๆ ได้และแน่นอนว่าเราไม่สามารถรู้ได้ว่าการสุ่มแบบไหนจะให้รูปที่เราต้องการได้ จึงต้องใช้ CLIP คอยกำกับและค่อย ๆ เปลี่ยน Random input เหล่านี้ให้เป็นรูปที่เราต้องการ,\n- วิธี #1: เริ่มจากการเทรน CLIP ขึ้นมาเองใช้ข้อมูลเริ่มจาก flicker8k (8,000 รูป) ไปจนถึง flicker30k (30,000 รูป) แปลข้อมูล caption จากภาษาอังกฤษไปไทยด้วย PyThaiNLP; ใช้ resnet-50 เป็น image encoder และ WangchanBERTa เป็น text encoder (ThCLIP),\n- วิธีแรกยังไม่ได้ผลเป็นที่น่าพึงพอใจด้วยปัจจัยขนาดชุดข้อมูลและเวลาในการเทรน จึงทดลองวิธี knowledge distillation สำหรับ CLIP แทน,\n- วิธี #2: เทรนใหม่โดยการสอนให้ ThCLIP สร้าง text embeddings ให้คล้ายกับ OpenAI CLIP มากที่สุดตาม mean-squared error loss; ใช้ปริมาณข้อมูลน้อยกว่าและได้ผลดีกว่ามาก,\n- เทรนตามวิธี #2 ด้วยข้อมูล 2 ล้านรูป สุ่มจาก GCC, MSCOCO เหมือนของ SwedishCLIP,\n- จากการ \"ทดลอง ทดลอง ทดลอง\" พบว่า transform ภาพโดยสุ่มเพิ่มระดับ sharpness ให้กับภาพทำให้กราฟ Loss converge เร็วขึ้น, iteration ที่เหมาะที่สุดอยู่ระหว่าง 200–300 รอบ, รวมถึง:,\n- ใช้ negative prompt เพื่อพัฒนาคุณภาพรูปภาพได้ เช่น เมื่อสร้างภาพ \"เครื่องบิน\" ให้ \"ภาพเบลอ\" เป็น negative prompt (ใส่เข้าไปใน loss function) จะทำให้ได้ภาพเครื่องบินที่ชัดขึ้น,\n- ใช้ aesthetic-predictor จาก pretrained model ที่ประเมิน \"ความสวย\" ของรูป และให้ความสวยเป็นส่วนหนึ่งของ loss function; ทำให้รูปที่ออกมาสวยขึ้น,\n- ทดสอบประสิทธิภาพโมเดลด้วยแบบสอบถามจาก 27 คน พบว่า VGQAN-ThCLIP (โมเดลของเรา) ทำได้ดีกว่า VQGAN-CLIP (pretrained จาก OpenAI) เมื่อรูปภาพถูกสร้างจากข้อความสั้นทั้งด้านความสอดคล้องและความหลากหลาย แต่ยิ่งข้อความยาวทำได้ดีกว่าในด้านความสอดคล้องแต่ด้อยกว่าในด้านความหลากหลาย,\n- โมเดลสามารถทำ prompting ได้เหมือน text-to-image ชั้นนำทั่วไป เช่น \"คฤหาสน์\", \"คฤหาสน์ แฟนตาซี\", \"คฤหาสน์ แฮรี่พอตเตอร์\" ฯลฯ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"ผู้เขียนมีความสนใจทางด้าน machine learning เป็นอย่างมากและยังมีความมุ่งมั่นที่จะทำให้สำเร็จ ปัจจุบัน machine learning \u0026 AI มีบทบาทกับเราแทบทุกด้าน แต่การจะทำให้ AI ใช้งานได้ในแต่ละด้านนั้นแตกต่างกันอย่างสิ้นเชิง ผู้เขียนจึงอยากเก็บเกี่ยวประสบการณ์ตั้งแต่การสร้างไปจนถึงการนำไปใช้ของ Machine learning \u0026 AI ในแต่ละด้านเพื่อขยายขอบเขตไอเดียของตัวเองและเมื่อไอเดียที่เข้าท่ามาถึง ผู้เขียนก็สามารถลงมือทำได้เลย โดยรู้ว่าด้านที่จะทำนั้นต้องใช้ model ประมาณนี้ รู้แหล่งชุดข้อมูลและรู้คีย์เวิร์ดที่จะศึกษาเพิ่มเติม นอกจากนั้นการเข้าโครงการนี้จะทำให้เราได้เจอกับเมนเทอร์และเพื่อนร่วมโครงการที่มีความชอบ เหมือนๆ กัน เมื่อเค้ามีความถนัดในด้าน machine learing ที่เราจะทำเราก็สามารถขอคำแนะนำจากเค้าได้และในทางกลับกันเราก็สามารถให้คำแนะนำในด้านที่เราถนัดแก่เพื่อนร่วมโครงการได้เช่นกัน เป้าหมายของผู้เขียนคือการสร้างนวัตกรรมหรือสิ่งประดิษฐ์ที่ทุกคนสามารถใช้ได้อย่างแพร่หลายและเกิดประโยชน์จากการใช้งานนั้น ซึ่งปัจจุบันผู้เขียนอยากศึกษาเพิ่มเติมทางด้าน Machine learning \u0026 AI อยากลองศึกษาศาสตร์แขนงใหม่ๆของ machine learing อาทิเข่น NLP, time series, GAN และอยากศึกษาวิธีการนำไปปรับใช้กับปัญหาในชีวิตจริง  อยากทำการสร้างรูปสังเคราะห์จากข้อความภาษาไทย (text to image genarator) เพื่อจำลองการออกแบบผลิตภัณฑ์เบื้องต้นจากไอเดียแล้วนำไปประเมิณว่าสามารถนำไปต่อยอดได้มากเพียงใดหรือเพื่อค้นพบไอเดียใหม่จากรูปที่สังเคราะห์ขึ้นมา เช่น อยากออกแบบดีไซน์เก้าอี้จึงพิมพ์ไปว่าเก้าอี้ทรงทุเรียน ตัวโมเดลอาจจะให้ผลลัพธ์เป็นเก้าอี้ที่มีหนามทุเรียนเป็นขาหรือเก้าอี้ที่ใช้หนามมนเป็นที่นั่ง และอื่นๆที่ผู้เขียนคาดไม่ถึง ชุดข้อมูลรูป ใช้จาก COCO โดยส่วนมากจะเป็นรูปสิ่งของต่างๆ, ชุดข้อมูลคำ ใช้คำที่ผ่านการ embedded มาแล้วโดยใช้ thai2vec ด้วย PyThaiNLP, นอกจากนี้ถ้าเปลี่ยนชุดข้อมูลใหม่โดยใช้รูปหน้าคนแล้วเทรนให้โมเดลสร้างหน้าคนจากคำบอกเล่าของพยานก็จะสามารถสร้างรูปคนร้ายเพื่อใช้ในการตามหาตัวหรือทำรูปติดประกาศจับ การทำแบบนี้จะสามารถลดระยะเวลาการสเก็ตช์ภาพขั้นต้นและสามารถโฟกัสกับการปรับแต่งขั้นสุดท้ายให้ภาพตรงกับคนร้ายที่พยานเห็นมากที่สุด ก็เป็นอีกโครงงานหนึ่งที่น่าทำเช่นกัน\"","date":"12-7-22","title":"Text-to-image synthesis with VQGAN-ThCLIP","builder":"ภูริช ศิริทิพย์ 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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จากนั้นใช้ประสบการณ์การแต่งเพลง สร้างกฎเปลี่ยนคำทำนายกลับเป็น PBW และ PBY,\n- สำหรับ feature ในการทำนาย ใช้ความยาวและพิชจากโน้ตทั้งสองตัวสร้างขึ้นด้วย pyUTAU,\n- ใช้ baseline เป็นการสร้าง pitchbends ด้วย Portamento ใน UTAU คือแค่ลากเส้นขึ้น-ลงแบบเป็นเส้นตรง แน่นอนว่าจะได้เสียงที่ไม่เป็นธรรมชาตินัก,\n- ใช้ random forest ได้ accuracy 61% บน test set เทียบกับ 27% ของ Portamento baseline จาก 63 classes,\n- สังเกตว่าโมเดลทาย class 0 (ไม่มีพิช) และ 1 (พิชลง) มากกว่าปกติมาก (ทั้งสองคลาสเป็น 2/3 ของตัวอย่างทั้งหมด) จึงลองสร้างโมเดล logistic regression เพื่อดูว่าโมเดลคิดอย่างไร; พบว่าสำหรับ 0 โมเดลมองว่าถ้าโน้ตตัวหน้าเป็น rest แทบจะแน่นอนว่าต้องทายว่าไม่มีพิช สำหรับ 1 โมเดลมองว่าถ้าโน้ตตัวหน้าสั้นกว่าส่วนใหญ่จะเป็นพิชลง ซึ่งตรงกับสัญชาติญาณของนักแต่งเพลงที่เป็นมนุษย์\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"What inspires me to create AI is how I discovered NLP by accident while I was looking to create spoonerism for Thai words. Back then I really wonder how a library like PyThaiNLP can split syllables nearly perfectly without me having to tell the users to split on my own, and that really get me obsessed.\"","date":"12-8-22","title":"Using Machine Learning to create Auto Pitch Writer for UTAU","builder":"จิรา กุลจิราพงษ์ (จิรา)","builder_info":"","thumbnail":"/images/2022/63/01.jpg","links":{"github":"https://github.com/CCSleep/utau-pitch-ml/","facebook":"https://facebook.com/aibuildersx/posts/450681343766977","blog":"https://medium.com/@CCSleep/using-machine-learning-to-create-auto-pitch-writer-for-utau-eec2d104236a"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Using-Machine-Learning-to-create-Auto-Pitch-Writer-for-UTAU"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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ปัญหาที่ต้องกาจะแก้คือการทำให้เพลงที่สร้างด้วยโปรแกรม \"ฟังเป็นธรรมชาติขึ้น\" เนื่องจากหากเราแค่ใส่พิชของแต่ละตัวโน้ตต่อกันไปเรื่อยๆจะทำให้ได้เพลงที่เหมือนหุ่นยนต์ร้อง จึงต้องมีการปรับพิชระหว่างตัวโน้ต (pitchbends) ซึ่งปกติทำด้วยมือคนแต่ง,\n- เก็บข้อมูลจากลิสต์ไฟล์ UST (UTAU sequence text) ที่ถูกรวบรวมไว้ที่ https://docs.google.com/document/d/1yKn3jN3rLoVFSXcPUET_iYsmbUi-nThRktgIAyXc230/edit และใช้ไฟล์ที่ถูกเก็บด้วย Mediafire ทั้งหมด,\n- UTAU แสดง pitchbends ด้วยตัวแปร 3 ตัวในรูปแบบ, , PBS=-66;-50 (เวลาเริ่ม;พิชเริ่ม), PBW=38,71,-3,141,50 (ค่าบนแกน Y นั่นคือแกนพิช สำหรับจุดถัดไป ในที่นี้คือ 4 จุด), PBY=-17.9,-18.6,-0.7,0,0 (ค่าความห่างจากจุดที่แล้วตามแกน X นั่นคือแกนเวลา), ,\n- ก่อนอื่นปรับ PBS ด้วยกฎโดยให้เวลาเริ่มคือเริ่มจาก 20% สุดท้ายของความยาวโน้ตตัวที่แล้ว และเริ่มจากพิชของโน้ตตัวที่แล้ว,\n- สำหรับ PBW และ PBY นั้น ใช้วิธีการสร้างโมเดล machine learning เพื่อทำนาย \"เทรนด์การขึ้นลง\" ของ PBY (ขึ้นเป็น 1 ลงเป็น 0; ตัวเลข 4 ตัว รวม 63 คลาส) เช่น [0,1,0,0], [0,1,1,1], ...,\n- จากนั้นใช้ประสบการณ์การแต่งเพลง สร้างกฎเปลี่ยนคำทำนายกลับเป็น PBW และ PBY,\n- สำหรับ feature ในการทำนาย ใช้ความยาวและพิชจากโน้ตทั้งสองตัวสร้างขึ้นด้วย pyUTAU,\n- ใช้ baseline เป็นการสร้าง pitchbends ด้วย Portamento ใน UTAU คือแค่ลากเส้นขึ้น-ลงแบบเป็นเส้นตรง แน่นอนว่าจะได้เสียงที่ไม่เป็นธรรมชาตินัก,\n- ใช้ random forest ได้ accuracy 61% บน test set เทียบกับ 27% ของ Portamento baseline จาก 63 classes,\n- สังเกตว่าโมเดลทาย class 0 (ไม่มีพิช) และ 1 (พิชลง) มากกว่าปกติมาก (ทั้งสองคลาสเป็น 2/3 ของตัวอย่างทั้งหมด) จึงลองสร้างโมเดล logistic regression เพื่อดูว่าโมเดลคิดอย่างไร; พบว่าสำหรับ 0 โมเดลมองว่าถ้าโน้ตตัวหน้าเป็น rest แทบจะแน่นอนว่าต้องทายว่าไม่มีพิช สำหรับ 1 โมเดลมองว่าถ้าโน้ตตัวหน้าสั้นกว่าส่วนใหญ่จะเป็นพิชลง ซึ่งตรงกับสัญชาติญาณของนักแต่งเพลงที่เป็นมนุษย์\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"What inspires me to create AI is how I discovered NLP by accident while I was looking to create spoonerism for Thai words. Back then I really wonder how a library like PyThaiNLP can split syllables nearly perfectly without me having to tell the users to split on my own, and that really get me obsessed.\"","date":"12-8-22","title":"Using Machine Learning to create Auto Pitch Writer for UTAU","builder":"จิรา กุลจิราพงษ์ (จิรา)","builder_info":"","thumbnail":"/images/2022/63/01.jpg","links":{"github":"https://github.com/CCSleep/utau-pitch-ml/","facebook":"https://facebook.com/aibuildersx/posts/450681343766977","blog":"https://medium.com/@CCSleep/using-machine-learning-to-create-auto-pitch-writer-for-utau-eec2d104236a"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"Using-Machine-Learning-to-create-Auto-Pitch-Writer-for-UTAU"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Violence Detection</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->ชินวัตร นาไชยธง (ม่อน)<!-- --> • </h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">WanchanBERTa Thai Grammarly</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->อิทธิพัฒน์ ปานขำ (มาร์จิ้น)<!-- --> • </h4><style data-emotion="css 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อุหนุน (อุดหนุน), จงใจพิมพ์ผิด; นะ (น้า), ณ๊อง (น้อง), พิมพ์ไม่ครบ; อลัง (อลังการ), แบต (แบตเตอรี) เป็นต้น รวม 42,893 ประโยคที่มีการสะกดผิด,\n- ทำความสะอาดข้อมูลโดย เปลี่ยนรูปแบบประโยคจาก \"สวัสดี|\u003cmsp value=”ครับ”\u003eค้าบ\u003c/msp\u003e|พี่|\u003cne\u003eจอม\u003c/ne\u003e\" เป็น \"สวัสดี^ครับ$พี่จอม\", เพิ่ม token สำหรับคำที่สะกดถูกเพื่อให้สามารถเติมคำได้ใน token เดียว, หาก token ที่สะกดผิดมีมากกว่าที่สะกดถูก ให้เติม _ ไปให้ครบเท่ากัน,\n- ทดลองใช้ hunspell, seq2seq และ tagging and masking,\n- tagging and masking ทำได้ดีที่สุด; โมเดลทำงานด้วยการชี้เป้า token ที่สะกดผิด (tagging; token classification) แล้วแทนที่ด้วย mask token จากนั้นให้โมเดลเดาว่า mask นั้นควรจะเป็นอะไร (masking),\n- ได้ accuracy 28.1% / F1 score 0.256 เทียบกับ hunspell และ seq2seq ที่แทบทายไม่ถูกเลย; ถ้าดูจาก BLEU รายประโยค จาก 1,000 ประโยคใน test set โมเดล tagging and masking แก้ถูก 386 ประโยค\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e 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อุหนุน (อุดหนุน), จงใจพิมพ์ผิด; นะ (น้า), ณ๊อง (น้อง), พิมพ์ไม่ครบ; อลัง (อลังการ), แบต (แบตเตอรี) เป็นต้น รวม 42,893 ประโยคที่มีการสะกดผิด,\n- ทำความสะอาดข้อมูลโดย เปลี่ยนรูปแบบประโยคจาก \"สวัสดี|\u003cmsp value=”ครับ”\u003eค้าบ\u003c/msp\u003e|พี่|\u003cne\u003eจอม\u003c/ne\u003e\" เป็น \"สวัสดี^ครับ$พี่จอม\", เพิ่ม token สำหรับคำที่สะกดถูกเพื่อให้สามารถเติมคำได้ใน token เดียว, หาก token ที่สะกดผิดมีมากกว่าที่สะกดถูก ให้เติม _ ไปให้ครบเท่ากัน,\n- ทดลองใช้ hunspell, seq2seq และ tagging and masking,\n- tagging and masking ทำได้ดีที่สุด; โมเดลทำงานด้วยการชี้เป้า token ที่สะกดผิด (tagging; token classification) แล้วแทนที่ด้วย mask token จากนั้นให้โมเดลเดาว่า mask นั้นควรจะเป็นอะไร (masking),\n- ได้ accuracy 28.1% / F1 score 0.256 เทียบกับ hunspell และ seq2seq ที่แทบทายไม่ถูกเลย; ถ้าดูจาก BLEU รายประโยค จาก 1,000 ประโยคใน test set โมเดล tagging and masking แก้ถูก 386 ประโยค\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e 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diff --git a/2022/vTranslator-Transcribe-and-Translate-VTuber-using-Wav2Vec2.html b/2022/vTranslator-Transcribe-and-Translate-VTuber-using-Wav2Vec2.html
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--- a/2022/vTranslator-Transcribe-and-Translate-VTuber-using-Wav2Vec2.html
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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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index 6f7b03d..fec221b 100644
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+++ "b/2022/\340\270\252\340\270\243\340\271\211\340\270\262\340\270\207\340\270\252\340\270\243\340\270\243\340\270\232\340\270\227\340\271\200\340\270\236\340\270\245\340\270\207-Undertale-\340\270\234\340\271\210\340\270\262\340\270\231-LSTM-\340\271\201\340\270\245\340\270\260-Teacher-Forcing-RNN.html"
@@ -1 +1 @@
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Forcing,\n- ในวัยเด็กผมเคยมีประสบการณ์เล่มเกมที่มีชื่อว่า Undertale มันเป็นเกมที่มีเนื้อเรื่องแปลกใหม่ ระบบการเล่นที่สนุก และที่สำคัญที่สุด มันมีเพลงประกอบตัวเกมที่ไพเราะเกินบรรยาย เพลงประกอบเกมนี้ได้กวาดรางวัลมาแล้วมากมาย ขายเป็นแผ่นเสียงได้เป็นกอบเป็นกำและได้ถูกจัดแสดงบนเวทีระดับโลกมาแล้ว ตัวผมจึงอยากลองค้นหาความมหัศจรรย์ของบทเพลงเหล่านี้ ทว่าผมขาดความรู้และพรสวรรค์ทางด้านดนตรีจึงไม่สามารถเข้าใจความสัมพันธ์ของบทเพลงเหล่านี้ได้ ผมจึงลองศึกษาศาสตร์AI ในการวิเคราะห์ความสัมพันธ์เหล่านี้ดู,\n- ใช้ dataset ที่เป็น MIDI ของเพลงเกม Undertale จาก Kaggle,\n- พบปัญหาว่า 1) มีเครื่องดนตรีเล่นพร้อมกันหลาย track ใน 1 file midi ทำให้ยากต่อการเลือก track ที่มีความสำคัญมากที่สุด 2) resolution (โน้ตถูกแบ่งเป็นกี่ส่วน) ที่กระจายตัวหลากหลาย ค่า resolution ที่มากทำให้สามารถอ่านข้อมูลได้ช้า และสิ้นเปลืองพื้นที่หน่วยความจำ,\n- แก้ปัญหาโดยการปรับ resolution ให้เป็น 96 ทั้งหมด (เพิ่ม tempo เป็นการทดแทน) และแปลงไฟล์midi ให้เหลือเพียง 1 track และมีเพียง 1 เสียงเครื่องดนตรีด้วย pianoroll (แล้วค่อยเปลี่ยนกลับเป็น MIDI อีกรอบ),\n- ใช้สถาปัตยกรรม LSTM (1-3 ชั้น), BiLSTM (3 ชั้น) และทดลองเทคนิค warm-start (เทรนต่อจากโมเดลคล้ายคลึงกัน) และ teacher forcing,\n- teacher forcing เป็นเทคนิคที่ใช้ ground truth เป็น input ให้กับ RNN (ในที่นี้คือ LSTM) ในหน่วยถัดไปแทนที่จะเป็น output จากหน่วยก่อนหน้า,\n- วัดผลด้วยแบบสอบถามและคำนวณ mean opinion score; พบว่า WarmStart + BiThreeFold (BiLSTM 3 ชั้นและ warm start; 3.68), WarmStart (warmstart + teacher forcing; 3.59), BiThreeFold (BiLSTM 3 ชั้น; 3.34) และ Toby (LSTM 1 ชั้น; 3.30) ทำคะแนนได้ดีกว่าเพลงจริง (2.80) เสียอีก(!!) ทั้งนี้การประเมินผลอาจจะมี bias เนื่องจากความหลากหลายและประสบการณ์ของผู้ทำแบบสอบถาม,\n- โมเดลไม่สามารถเรียนรู้จังหวะ, ความยาวของโน๊ต และไม่สามารถแต่งเพลงที่มีความหลากหลายของจังหวะได้ อาจจะส่งผลต่อความรู้สึกต่อคุณภาพของเพลงของผู้ตอบแบบสอบถาม เนื่องจากว่าความไพเราะของเพลงมีเรื่องจังหวะและทำนองเข้ามาเกี่ยวข้องด้วย,\n- โมเดลอาจจะ overfit บทเพลงและยังไม่สามารถแต่งเพลงให้หลากหลายตามอารมณ์ได้; 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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Forcing,\n- ในวัยเด็กผมเคยมีประสบการณ์เล่มเกมที่มีชื่อว่า Undertale มันเป็นเกมที่มีเนื้อเรื่องแปลกใหม่ ระบบการเล่นที่สนุก และที่สำคัญที่สุด มันมีเพลงประกอบตัวเกมที่ไพเราะเกินบรรยาย เพลงประกอบเกมนี้ได้กวาดรางวัลมาแล้วมากมาย ขายเป็นแผ่นเสียงได้เป็นกอบเป็นกำและได้ถูกจัดแสดงบนเวทีระดับโลกมาแล้ว ตัวผมจึงอยากลองค้นหาความมหัศจรรย์ของบทเพลงเหล่านี้ ทว่าผมขาดความรู้และพรสวรรค์ทางด้านดนตรีจึงไม่สามารถเข้าใจความสัมพันธ์ของบทเพลงเหล่านี้ได้ ผมจึงลองศึกษาศาสตร์AI ในการวิเคราะห์ความสัมพันธ์เหล่านี้ดู,\n- ใช้ dataset ที่เป็น MIDI ของเพลงเกม Undertale จาก Kaggle,\n- พบปัญหาว่า 1) มีเครื่องดนตรีเล่นพร้อมกันหลาย track ใน 1 file midi ทำให้ยากต่อการเลือก track ที่มีความสำคัญมากที่สุด 2) resolution (โน้ตถูกแบ่งเป็นกี่ส่วน) ที่กระจายตัวหลากหลาย ค่า resolution ที่มากทำให้สามารถอ่านข้อมูลได้ช้า และสิ้นเปลืองพื้นที่หน่วยความจำ,\n- แก้ปัญหาโดยการปรับ resolution ให้เป็น 96 ทั้งหมด (เพิ่ม tempo เป็นการทดแทน) และแปลงไฟล์midi ให้เหลือเพียง 1 track และมีเพียง 1 เสียงเครื่องดนตรีด้วย pianoroll (แล้วค่อยเปลี่ยนกลับเป็น MIDI อีกรอบ),\n- ใช้สถาปัตยกรรม LSTM (1-3 ชั้น), BiLSTM (3 ชั้น) และทดลองเทคนิค warm-start (เทรนต่อจากโมเดลคล้ายคลึงกัน) และ teacher forcing,\n- teacher forcing เป็นเทคนิคที่ใช้ ground truth เป็น input ให้กับ RNN (ในที่นี้คือ LSTM) ในหน่วยถัดไปแทนที่จะเป็น output จากหน่วยก่อนหน้า,\n- วัดผลด้วยแบบสอบถามและคำนวณ mean opinion score; พบว่า WarmStart + BiThreeFold (BiLSTM 3 ชั้นและ warm start; 3.68), WarmStart (warmstart + teacher forcing; 3.59), BiThreeFold (BiLSTM 3 ชั้น; 3.34) และ Toby (LSTM 1 ชั้น; 3.30) ทำคะแนนได้ดีกว่าเพลงจริง (2.80) เสียอีก(!!) ทั้งนี้การประเมินผลอาจจะมี bias เนื่องจากความหลากหลายและประสบการณ์ของผู้ทำแบบสอบถาม,\n- โมเดลไม่สามารถเรียนรู้จังหวะ, ความยาวของโน๊ต และไม่สามารถแต่งเพลงที่มีความหลากหลายของจังหวะได้ อาจจะส่งผลต่อความรู้สึกต่อคุณภาพของเพลงของผู้ตอบแบบสอบถาม เนื่องจากว่าความไพเราะของเพลงมีเรื่องจังหวะและทำนองเข้ามาเกี่ยวข้องด้วย,\n- โมเดลอาจจะ overfit บทเพลงและยังไม่สามารถแต่งเพลงให้หลากหลายตามอารมณ์ได้; 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--- "a/2022/\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245-CNN-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\270\201\340\270\262\340\270\243\340\270\210\340\270\263\340\271\201\340\270\231\340\270\201\340\270\252\340\270\261\340\270\215\340\270\215\340\270\262\340\270\223\340\270\252\340\270\241\340\270\255\340\270\207\340\271\203\340\270\231\340\270\243\340\270\260\340\270\232\340\270\232-SSVEP-BCI-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\271\204\340\270\241\340\271\200\340\270\201\340\270\243\340\270\231-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine).html"
+++ "b/2022/\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245-CNN-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\270\201\340\270\262\340\270\243\340\270\210\340\270\263\340\271\201\340\270\231\340\270\201\340\270\252\340\270\261\340\270\215\340\270\215\340\270\262\340\270\223\340\270\252\340\270\241\340\270\255\340\270\207\340\271\203\340\270\231\340\270\243\340\270\260\340\270\232\340\270\232-SSVEP-BCI-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\271\204\340\270\241\340\271\200\340\270\201\340\270\243\340\270\231-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine).html"
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CNN สำหรับการจำแนกสัญญาณสมองในระบบ SSVEP-BCI สำหรับไมเกรน (A CNN for Classification Task in SSVEP-BCI for Migraine)"/><meta property="og:description" content="ฆนัท บุญจง (เค) • "/><meta property="og:image" content="https://ai-builders.github.io/showcase/images/2022/56/01.jpg"/><meta property="og:site_name" content="AI Builders Showcase"/><meta name="next-head-count" content="17"/><link rel="preload" href="/showcase/_next/static/css/f9f072bebc05078a.css" as="style"/><link rel="stylesheet" href="/showcase/_next/static/css/f9f072bebc05078a.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/showcase/_next/static/chunks/polyfills-5cd94c89d3acac5f.js"></script><script src="/showcase/_next/static/chunks/webpack-74b12628e711d77e.js" defer=""></script><script src="/showcase/_next/static/chunks/framework-5f4595e5518b5600.js" defer=""></script><script src="/showcase/_next/static/chunks/main-e95b58999d220b83.js" defer=""></script><script 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หรือการให้ผู้ป่วยดูภาพ/เสียงและบันทึกคลื่นสมองผ่าน BCI (brain-computer interface),\n- ใช้ชุดข้อมูลคนเป็มไมเกรน 17 คนและไม่เป็นไมเกรน 18 คนจากงานวิจัย Zar et al (2020; https://kilthub.cmu.edu/articles/dataset/Ultra_high-density_EEG_recording_of_interictal_migraine_and_controls_sensory_and_rest/12636731),\n- ใช้ 60 Hz notch filter เพื่อลด noise ในข้อมูลสัญญาณ; ใช้ sampling rate ที่ 512 Hz และทดลองแยกแยะสัญญาณด้วย window 30 และ 4 วินาที; แบ่ง train-valid-test ที่ 64:16:20,\n- ใช้สถาปัตยกรรม EEGNet ในการเทรน; โมเดลประกอบด้วย 2D convolution, depthwise 2D convolution และ separable 2D convolution layers; https://arxiv.org/abs/1611.08024,\n- สำหรับ window 30 วินาที ได้ accuracy ดีกว่า SVM (51.4%) และ XGBoost (54.8%) ที่ 74% และ 87.5% สำหรับ window 4 วินาที\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e \"\"เนื่องจากผมเป็นคนที่สนใจและถนัดในชีววิทยา ที่ผ่านมาจึงเข้าร่วมการแข่งขันทางวิชาการหลายๆอย่างทั้งโอลิมปิกวิชาการ ตอบปัญหาชีววิทยา/การแพทย์ 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ซึ่งการทำงานนี้เป็นส่วนของ Computational Biophysics ที่ต้องอาศัยการเขียนโปรแกรมเข้ามาช่วยวิเคราะห์โครงสร้าง DNA ผมจึงจะได้มีโอกาสทำงานใช้ ภาษา python และคิดว่า ML อาจสามารถนำมาประยุกต์ใช้ในงานได้ไม่มากก็น้อย  สาเหตุที่ผมอยากเข้าโครงการ คือ การที่ AI และ Machine Learning จะเข้ามามีบทบาทความสำคัญในอนาคตเป็นอย่างมาก ไม่ว่าจะเป็นในเชิงการแพทย์ วิศวกรรม การทำธุรกิจ ฉะนั้น การเรียนรู้ทักษะการเขียนโปรแกรมเพื่อพัฒนา AI เบื้องต้นจึงจะเป็นทักษะที่จำเป็น ยิ่งไปกว่านั้นคือ การหาประสบการณ์ในการทำ AI เพื่อนำมาใช้แก้ปัญหาจริง จะช่วยให้เห็นแนวทางที่จะนำไปต่อยอดเพื่อให้เกิดประโยชน์ในอนาคตมากยิ่งขึ้นไป โดยผมเห็นว่าโครงการนี้สามารถตอบโจทย์ เพราะถ้าได้เข้าร่วมผมจะได้ผู้เชี่ยวชาญคอยชี้แนะและสอนการทำงานในสายนี้จริงๆ ซึ่งอาจทำให้เราได้เรียนรู้ในสิ่งที่ลึกกว่าการเรียนจากแหล่งข้อมูลทั่วไปในอินเตอร์เน็ต นอกจากนี้ ผมยังเห็นว่า การเข้าโครงการจะช่วยให้เรามี connection กับเพื่อนที่สนใจใน AI เหมือนกัน และรู้จักกับอาจารย์ต่างๆ ซึ่งจะเป็นประโยชน์มาก เพราะอาจช่วยให้ผมมีโอกาสได้ partner ทำงานวิจัย หรือทำธุรกิจเทคโนโลยีที่ได้สร้างจากประสบการณ์การเข้าร่วมโครงการและการศึกษาต่อเพิ่มเติม\"","date":"5-8-22","title":"โมเดล CNN สำหรับการจำแนกสัญญาณสมองในระบบ SSVEP-BCI สำหรับไมเกรน (A CNN for Classification Task in SSVEP-BCI for Migraine)","builder":"ฆนัท บุญจง (เค)","builder_info":"","thumbnail":"/images/2022/56/01.jpg","links":{"github":"https://github.com/KhanutBJ/Migraine_CNN","facebook":"https://facebook.com/aibuildersx/posts/438384788329966","blog":"https://medium.com/@vwgprvvtsf/showcase-120bc69fb720"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2022","id":"โมเดล-CNN-สำหรับการจำแนกสัญญาณสมองในระบบ-SSVEP-BCI-สำหรับไมเกรน-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine)"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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ซึ่งการทำงานนี้เป็นส่วนของ Computational Biophysics ที่ต้องอาศัยการเขียนโปรแกรมเข้ามาช่วยวิเคราะห์โครงสร้าง DNA ผมจึงจะได้มีโอกาสทำงานใช้ ภาษา python และคิดว่า ML อาจสามารถนำมาประยุกต์ใช้ในงานได้ไม่มากก็น้อย  สาเหตุที่ผมอยากเข้าโครงการ คือ การที่ AI และ Machine Learning จะเข้ามามีบทบาทความสำคัญในอนาคตเป็นอย่างมาก ไม่ว่าจะเป็นในเชิงการแพทย์ วิศวกรรม การทำธุรกิจ ฉะนั้น การเรียนรู้ทักษะการเขียนโปรแกรมเพื่อพัฒนา AI เบื้องต้นจึงจะเป็นทักษะที่จำเป็น ยิ่งไปกว่านั้นคือ การหาประสบการณ์ในการทำ AI เพื่อนำมาใช้แก้ปัญหาจริง จะช่วยให้เห็นแนวทางที่จะนำไปต่อยอดเพื่อให้เกิดประโยชน์ในอนาคตมากยิ่งขึ้นไป โดยผมเห็นว่าโครงการนี้สามารถตอบโจทย์ เพราะถ้าได้เข้าร่วมผมจะได้ผู้เชี่ยวชาญคอยชี้แนะและสอนการทำงานในสายนี้จริงๆ ซึ่งอาจทำให้เราได้เรียนรู้ในสิ่งที่ลึกกว่าการเรียนจากแหล่งข้อมูลทั่วไปในอินเตอร์เน็ต นอกจากนี้ ผมยังเห็นว่า การเข้าโครงการจะช่วยให้เรามี connection กับเพื่อนที่สนใจใน AI เหมือนกัน และรู้จักกับอาจารย์ต่างๆ ซึ่งจะเป็นประโยชน์มาก เพราะอาจช่วยให้ผมมีโอกาสได้ partner ทำงานวิจัย 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">pimthaigans</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Supawit Marayat<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- เชียงราย</h4><style data-emotion="css 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ที่ถูกอัดโดยเครื่องมือที่มีคุณภาพไม่ค่อยเจ๋งนัก จึงทำให้เพลงมีความถี่ต่ำ และมีมิติน้อย มีเสียงรบกวนเต็มไปหมด ซึ่งเต็มไปด้วยความไม่เพอร์เฟ็กต์เต็มหมด ในวันที่เราไปไกลกับเพลงคุณภาพเยี่ยมอย่าง Hi-Fi จนมันตันแล้ว ทุกอย่างเพอร์เฟ็กต์ไปหมดแล้วสำหรับตอนนี้ เราเลยหันกลับมาหาอะไรที่มันไม่เพอร์เฟ็กต์ดูบ้าง เพราะความไม่เพอร์เฟ็กต์มีเสน่ห์ในตัวมันเองอย่างปฏิเสธไม่ได้\n- เป้าหมายของโมเดลคือการลดแรงงานคนในการเปลี่ยนเพลงเป็น Lo-Fi\n- สร้างชุดข้อมูลด้วยการอัดเสียง desktop โดยใช้โปรแกรม audacity ในไลฟ์ของช่อง Lo-Fi girl บน youtube\n- source audio ใช้ GTZAN Dataset ซึ่งได้ใช้เพลงทั้งหมด 10 ประเภท 1. blues 2. classical 3. country 4. disco 5. hiphop 6. jazz 7. metal 8. rock 9. pop 10. reggae โดยใช้ประเภทละ50เพลง คิดเป็น 500 ไฟล์\n- target audio ได้อัดไปทั้งสิ้นเป็นเวลา 7 ชั่วโมง ได้ตัดช่วงเวลาที่ไม่มีเสียงออกไป และทำการแบ่งระยะเวลาช่วงละ30วินาที โดยได้เสียงมาทั้งหมด 800 ไฟล์ ไฟล์ละ 30วินาที รวมทั้งสิ้น 6 ชั่วโมง 40 นาที\n- ใช้สถาปัตยกรรม MelGAN-VC ในการเปลี่ยน source audio เป็น target audio; ข้อดีคือไม่จำเป็นต้องใช้ข้อมูลที่ถูกจับคู่กันและไม่ต้องกำหนดระยะเวลาของเสียงให้เหมือนกันหมด\n- ผลที่ออกมาหลังจากเทรนไปได้ 52 epochs ได้สังเกตว่าหลังจากที่ generate เพลงออกมานั้นเสียงร้องถูกกลืนเข้าไปกับเสียงของเครื่องดนตรีจึงหาวิธีการแก้ไขด้วย Spleeter ที่เป็น library สำหรับแยกเสียงเครื่องดนตรีหรือเสียงร้อง จึงนำมาใช้ preprocess ข้อมูลก่อนการเทรน\n- ประเมินผลแยกเป็นแนวเพลง blues, rock และ country โดยให้คะแนน 1. ความเป็น Lo-Fi ของเพลง 2. เค้าโครงเดิมของเพลง; คะแนนอยู่ในช่วงประมาณ 3/5\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e ผมอยู่ในยุคมี่ ai เริ่มเข้ามามีบทบาทในชีวิตมากขึ้น และจะเพิ่มขึ้นต่อไปเรื่อยๆในอนาคร ทำให้ผมมีความสนใจในด้าน ai เป็นอย่างมาก ได้เห็นสิ่งต่างๆเกี่ยวกับaiที่น่าทึ่งมาก อย่างเช่น chatgpt ที่เราสามารถถามข้อมูลแทบได้ทุกอย่าง หรือ midjourney ที่สามารถ generate รูปภาพที่เราต้องการจากข้อความที่เราพิมพ์ไปได้จึงทำให้ผมอยากรู้ว่าสิ่งเหล่านั้นมันถูกสร้างขึ้นมาอย่างไร สามารถเรียนรู้ให้เหมือนมนุษย์ได้อย่างไร ในระดับที่เจาะลึกลงไปผมเคยลงแข่งขัน kidbright coding \u0026 ai simulator online 2023 เป็นการแข่งขันสั่งการหุ่นยนต์ให้เดินตามเสียงโดยเราต้องทำการtrainเพื่อให้บอกทางได้แม่นยำมากที่สุด ตัวผมขณะนั้นสนใจaiแต่เดิมอยู่แล้วพอมีงานแข่งนี้ก็ทำให้ยิ่งสนใจเข้าไปอีก แล้วได้มาเจอกับโครงการai builder จากคุณครูในโรงเรียนจึงเห็นโอกาสในการพัฒนาตนเองเสริมความรู้ในด้านai อยากเข้าร่วมโครงการนี้ ซึ่งถ้าผมได้เข้าร่วมผมมั่นใจว่าผมสามารถนำความรู้ที่โครงการถ่ายทอดไปประยุกต์ใช้ด้านต่างๆในชีวิตประจำวัน\n    ","date":"31-7-24","title":"Lo-Fi music style transfer","builder":"Thanakit Chongwilaikasem/มัธยมศึกษาปีที่ 4.0","builder_info":" สงขลา -- delta-ducks 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ที่ถูกอัดโดยเครื่องมือที่มีคุณภาพไม่ค่อยเจ๋งนัก จึงทำให้เพลงมีความถี่ต่ำ และมีมิติน้อย มีเสียงรบกวนเต็มไปหมด ซึ่งเต็มไปด้วยความไม่เพอร์เฟ็กต์เต็มหมด ในวันที่เราไปไกลกับเพลงคุณภาพเยี่ยมอย่าง Hi-Fi จนมันตันแล้ว ทุกอย่างเพอร์เฟ็กต์ไปหมดแล้วสำหรับตอนนี้ เราเลยหันกลับมาหาอะไรที่มันไม่เพอร์เฟ็กต์ดูบ้าง เพราะความไม่เพอร์เฟ็กต์มีเสน่ห์ในตัวมันเองอย่างปฏิเสธไม่ได้\n- เป้าหมายของโมเดลคือการลดแรงงานคนในการเปลี่ยนเพลงเป็น Lo-Fi\n- สร้างชุดข้อมูลด้วยการอัดเสียง desktop โดยใช้โปรแกรม audacity ในไลฟ์ของช่อง Lo-Fi girl บน youtube\n- source audio ใช้ GTZAN Dataset ซึ่งได้ใช้เพลงทั้งหมด 10 ประเภท 1. blues 2. classical 3. country 4. disco 5. hiphop 6. jazz 7. metal 8. rock 9. pop 10. reggae โดยใช้ประเภทละ50เพลง คิดเป็น 500 ไฟล์\n- target audio ได้อัดไปทั้งสิ้นเป็นเวลา 7 ชั่วโมง ได้ตัดช่วงเวลาที่ไม่มีเสียงออกไป และทำการแบ่งระยะเวลาช่วงละ30วินาที โดยได้เสียงมาทั้งหมด 800 ไฟล์ ไฟล์ละ 30วินาที รวมทั้งสิ้น 6 ชั่วโมง 40 นาที\n- ใช้สถาปัตยกรรม MelGAN-VC ในการเปลี่ยน source audio เป็น target audio; 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Praditukrit • มัธยมศึกษาปีที่ 5.0 -- สงขลา"/><meta property="og:image" content="https://ai-builders.github.io/showcase/images/2023/105/01.jpg"/><meta property="og:site_name" content="AI Builders Showcase"/><meta name="next-head-count" content="17"/><link rel="preload" href="/showcase/_next/static/css/f9f072bebc05078a.css" as="style"/><link rel="stylesheet" href="/showcase/_next/static/css/f9f072bebc05078a.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/showcase/_next/static/chunks/polyfills-5cd94c89d3acac5f.js"></script><script src="/showcase/_next/static/chunks/webpack-74b12628e711d77e.js" defer=""></script><script src="/showcase/_next/static/chunks/framework-5f4595e5518b5600.js" defer=""></script><script src="/showcase/_next/static/chunks/main-e95b58999d220b83.js" defer=""></script><script src="/showcase/_next/static/chunks/pages/_app-cafc0401ce7959b1.js" defer=""></script><script src="/showcase/_next/static/chunks/1bfc9850-327fe9449ffcca7e.js" 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Plank Form Checker</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Thee Kittivorapat<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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danielshanbalico/dog-vs-not-dog เพื่อป้องกันโมเดลทายมั่วกรณีไม่ใช่รูปสุนัข\n- แบ่ง train-valid-test split ที่ 80/10/10\n- ทดสอบการทำ image augmentation หลากหลายรูปแบบ ค้นพบว่า squish resize และค่าตั้งต้นของ fastai ทำได้ดีที่สุด\n- เปรียบเทียบสถาปัตยกรรม resnet34, resnet50, vgg16, และ densenet201 ปรากฎว่า resnet34 ได้ความแม่นยำสูงที่สุด\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e ต้องการพัฒนาตนเอง หาความรู้และประสบการณ์ใหม่ๆ สะสมความรู้ เพื่อในอนาคตจะสามารถนำความรู้ที่มีมาช่วยคนที่เรารักและเพื่อนมนุษย์อีกมากมายได้ดิฉันมีความตั้งใจและมุ่งมั่นที่จะเรียนรู้และฝึกฝนเป็นอย่างมากเพื่อที่จะสามารถนำความรู้ไปใช้ให้เกิดประโยชน์แก่ผู้คนได้มากที่สุด แม่ของดิฉันเป็นผู้ป่วยโรคไตทำให้ดิฉันได้เห็นความยากลำบากในการเลือกรับประทานอาหารเป็นอย่างมาก ทุกครั้งก่อนคุณแม่จะเลือกรับประทานอาหารต้องคอยหาข้อมูลก่อนเสมอว่าในอาหารเมนูนี้มีส่วนผสมอะไรบ้างและมีสารอาหารที่ส่งผลกระทบต่อไตหรือไม่ อาหารที่รับประทานบ่อยคุณแม่ก็จะจำได้แต่อาหารบนโลกนี้ไม่ได้มีแค่ 10-20 อย่าง 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Dog emotions</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Thirada Thomnam<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กำแพงเพชร</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Object detection for CCTV with traffic</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Kontuch Suksawat<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- สงขลา</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Drum Note Classification</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Pataranan Sethpakdee<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5 -- กรุงเทพมหานคร</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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encoder; สามารถนำไปใช้จริงได้ในเครื่องตัวเองผ่าน command line\n- เริ่มจากการที่มีไฟล์งานอยู่จำนวนมากแล้วเวลาที่ต้องการที่จะกลับมาแก้งานหรือมาดูเป็นตัวอย่างผมมักจะหาไฟล์ไม่เจอหรือใช้เวลานานมากโดย ทำให้อยากทำโปรแกรมที่ช่วยในการจัดไฟล์พวกนี้ให้ผมจะได้ไม้ต้องพลิกแผ่นดินหาไฟล์งานไฟล์เดียวอีก\n- วิธีการทำงานคือให้เลือก sample files ของแต่ละหมวดหมู่ที่ต้องการจัด หลังจากนั้นโมเดลจะทำการหาความคล้ายคลึงกันของทุก file ใน folder ที่กำลังจัดระเบียบกับ sample files ในแต่ละหมวด\n- เริ่มแรกใช้ข้อมูล 1,066 ไฟล์จาก 15 หมวดเอกสารราชการในการทดสอบ; แต่เนื่องจากบางหมวดหมู่มีเอกสารน้อยเกินไปจึงตัดเหลือเพียง 6 หมวดหมู่และทำความสะอาดเพิ่มเติมจนเหลือ 456 ไฟล์ ทำให้ความแม่นยำของการจัดหมวดหมู่เพิ่มขึ้นจาก 30% เป็น 52%\n- ต่อมาพบว่ามี 2 หมวดหมู่ที่ประเภทเอกสารใกลกันเกินไปจึงรวมเป็นหมวดหมู่ energy ทำให้ได้ความแม่นยำ 59%\n- ทดลองวัดผลด้วยการจัดไฟล์เองในฐานะมนุษย์มีความแม่นยำสูงกว่าโมเดลที่ 68% แต่ใช้เวลาถึง 14 นาที เทียบกับโมเดลที่ใช้เพียง 1 นาที; อาจสรุปได้ว่าโมเดลสามารถช่วยทุ่นแรงในการจัดไฟล์ได้ 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I was given a chance to make a big project for myself so I decided to make a file sorting program that is using data from the files it self I called it CL_sort.the reason is the way that I sort my files is quite bad I usually have a file that can fit in 2 driffent folder and I don't want to deal with that anymore.but with help from of people there I was able to make this project possible and learn new things along the way too.ย้อนกลับไปในปี 2019 ผมเป็นคนที่ชอบที่จะลองทำสิ่งใหม่ ๆ ที่ผมสนใจเช่น การทำโมเดลสามมิติและการสร้างเกม แต่ผมก็ค้นพบว่าผมไม่ถนัดทั้งสองด้านแลยหลังจากนั้นผมก็พบว่าการเขียนโปรแกรมนั้นเป็นสิ่งที่ผมรู้สึกว่ามันสนุกดี(การเขียนโปรแกรมเป็นหนึ่งในหลาย ๆ สิ่งที่ต้องใช้ในการสร้างเกม) ผมก็เลยเขียนโปรแกรม utility อยู่เรื่อย ๆ เมื่อมีไอเดียเข้ามาในหัวและทั้งหมดนั้นก็เปลียนไปหลังจากที่ได้เข้าสู่ AI Builders ผมก็ได้โอกาสที่จะได้ทำโปรเจคใหญ่ ผมก็เลยตัดสินใจที่จะทำโปรแกรมจัดไฟล์ที่ใช้ข้อมูลจากตัวไฟล์มาใช้ในการจัดไฟล์ผมก็เลยเรียกมันว่า CL_sortทำไมหรอ เพราะวิธีที่ผมจัดไฟล์นั้นมักจะเจอปัญหาที่ไฟล์1 ไฟล์สามารถจัดอยู่ในสองหมวดที่แตกต่างกันได้และผมไม่อยากเจอแบบนั้นอีกแล้วและด้วยความช่วยเหลือจากพี่ ๆ ผมก็สามารถทำให้โปรเจคนี้เป็นไปได้และได้เรียนรู้สิ่งต่าง ๆ อีกมากมาย\n","date":"31-7-24","title":"CL_sort เพื่อนช่วยจัดไฟล์ที่คุณตามหา!?","builder":"Surapot Sangasap","builder_info":"มัธยมศึกษาปีที่ 5 -- กรุงเทพมหานคร","thumbnail":"/images/2023/69/01.jpg","links":{"github":"https://github.com/NopeN0t/CL_sort","facebook":"https://www.facebook.com/aibuildersx/posts/pfbid0uHd2S11VWFAbJ5GK1J3V7RrtrUfQsMwxpBCSMZPu9XtnAj7rCsykrn7fDBhLhFNUl","blog":"https://medium.com/@top7748/cl-sort-%E0%B9%80%E0%B8%9E%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B8%99%E0%B8%8A%E0%B9%88%E0%B8%A7%E0%B8%A2%E0%B8%88%E0%B8%B1%E0%B8%94%E0%B9%84%E0%B8%9F%E0%B8%A5%E0%B9%8C%E0%B8%97%E0%B8%B5%E0%B9%88%E0%B8%84%E0%B8%B8%E0%B8%93%E0%B8%95%E0%B8%B2%E0%B8%A1%E0%B8%AB%E0%B8%B2-thai-version-58d43426b93e"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2023","id":"69-cl-sort"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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benign และ malignant\n- โมเดลสามารถจำแนกภาพได้ด้วย f1-score 0.92; การจำแนกส่วนภาพได้ Mean IoU 0.82\n- แรงจูงใจในการทำโครงงาน (ในคำพูดของนักเรียนเอง): “The motivation behind my breast cancer ultrasound image segmentation project stems from my deep desire to protect and care for my loved ones, especially my dear mommy 💖. I yearn for her to enjoy a long and healthy life so that we can continue creating cherished memories together. Through this project, I aim to contribute to early detection and improved treatment of breast cancer, ensuring that not only my mom but also countless individuals worldwide can experience more precious moments with their loved ones.“\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e หนูเคยเข้าแข่งขันศิลหกรรมระดับชาติ คร้งที่ 70 เกี่ยวกับ web application และมีประสบการณ์ในการทำเว็บไซต์ขายสินค้าเกี่ยวกับอุปกรณ์การแพทย์ (เตียงผู้ป่วย) โดยมีการสั่งซื้อและจองสินค้า มีระบบผู้ใช้งานและหนูชอบออกแบบเว็บไซต์ ux/ui ให้เหมาะสมกับผู้ใช้งาน รวมถึงการทำแคตตาล็อกและตัดต่อรูปสินค้าเพื่อแสดงให้ลูกค้ารับชม หนูมีทักษะภาษาอังกฤษที่พอใช้ได้ระดับนึง หนูเคยสอบ sat ที่ bangkok christian international school ได้คะแนน 1100 ซึ่งหนูมีแพลนจะไปสอบอีกครั้งในเดือนพฤษภาคม และสอบ ielts ในช่วงเดือนสิงหาคม หนูจึงคิดว่าการที่หนูจะนำเอาสิ่งที่หนูมีความรู้ติดตัวไปพัฒนาในด้านของ ai จึงเป็นสิ่งที่น่าสนใจอย่างมาก หนูคิดว่ามันเหมือนกับเวทมนต์ที่เราสามารถเสกอะไรก็ได้ออกมาตามที่เราต้องการ นั่นจึงเป็นเหตุผลที่หนูอยกาเข้าร่วมโครงการนี้ถึงแม้ว่าหนูอาจจะไม่ถนัดภาษาไพทอนมากนัก แต่หนูก็พร้อมที่จะเรียนรู้ได้เสมอ เพราะว่าเราคือ homo sapiens ไม่มีใครสามารถมาหยุดเราได้ค่ะในอนาคตหนูมีความฝันที่อยากจะเป็น software engineer ที่ silicon valley โดยหนูได้รับแรงบันดาลใจมาจาก craig federighi และ elon musk ความฝันอันสูงสุดของหนูคือการได้รับทุนป.ตรีเต็มจำนวนไปเรียนต่อที่ต่างประเทศ ที่ (university of toronto) หนูมีแพลนที่จะไปสอบ sat และ ielts ในช่วงกลางปีนี้เพื่อยื่นคะแนนเข้ามาหาลัยในต่างประเทศ หนูมีประสบการณ์ในการรับทำงานเกี่ยวกับการเขียนเว็บไซต์เกี่ยวกับอุปกรณ์การแพทย์ (เตียงผู้ป่วย) และการทำแคตตาลอกเพื่อขายสิ้นค้า โดยในหน้าเว็บจะมีการแสดงสินค้าเตียงผู้ป่วยหลายรุ่น เช่น pf01, pf04, etc. รวมถึงการสั่งซื้อสินค้าจากหน้าเว็บที่เข้ามา แต่เนื่องจากสถานการณ์การเงินที่บ้านไม่เอื้ออำนวย คุณแม่หนูต้องออกไปทำงานคนเดียวส่วนหนูต้องกู้เงินกยศ เดือนละ 1800 บาทและจำเป็นต้องดูแลน้องสาวอนุบาล 3 ทั้งหมด หนูต้องออกไปทำงานเพื่อนำมาจ่ายค่าเทอมให้ตนเองและน้องสาว หนูจึงกลายเป็นเสาหลักของบ้านไปโดยปริยาย แต่ถึงอย่างนั้นแม้ว่าชีวิตหนูจะต้องเจออะไรนักหนาสาหัสมาก็ตามหนูก็จะเข้มแข็งและไม่ยอมแพ้ค่ะไม่ว่าจะต้องแลกมากับอะไรก็ตามหนูก็จะยอมอุทิศเพื่อให้ความฝันของหนูสำเร็จ เพื่อที่จะสามารถดูแลคุณแม่และน้องสาว จากนั้นพาพวกเขาย้ายมาอยู่ที่ต่างประเทศจะได้สบายขึ้น หนูไม่อยากให้ครอบครัวลำบาก เพราะเรามีกันทั้งหมดแค่ 3 คน\n    ","date":"31-7-24","title":"Breast Cancer Ultrasound Image Segmentation Using U-Net","builder":"Suweeraya Noensai","builder_info":"มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร","thumbnail":"/images/2023/70/01.jpg","links":{"github":"https://github.com/nadiasuweer4ya/Breast_Cancer_Ultrasound_Image_Segmentation_Using_U-Net/","facebook":"https://www.facebook.com/aibuildersx/posts/pfbid0EoobSHFDLvVF6SJHvXjRbcDhxTQpM7g7gWwDBne2TFtuKzwZZ7KfBcYvriH8PZrEl","blog":"https://medium.com/@24098_79544/breast-cancer-ultrasound-segmentation-using-u-net-9b3435be019c"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2023","id":"70-breast-cancer-ultrasound-image-segmentation-using-u"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Breast Cancer Ultrasound Image Segmentation Using U-Net</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Suweeraya Noensai<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">โมเดลการแปลภาษามือไทยด้วย MediaPipe</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Arucha Khematharonon<!-- --> • <!-- -->มัธยมศึกษาปีที่ 6.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Sitting Posture Estimate</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Aritat Suriyapattanapong<!-- --> • <!-- -->มัธยมศึกษาปีที่ 4.0 -- สมุทรปราการ</h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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diff --git a/2023/81-pseudobulbar-palsy-detection-with-wav2vec2-and-openai-whisper.html b/2023/81-pseudobulbar-palsy-detection-with-wav2vec2-and-openai-whisper.html
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-<!DOCTYPE html><html><head><meta name="viewport" content="width=device-width"/><meta charSet="utf-8"/><link rel="apple-touch-icon" sizes="180x180" href="/showcase/favicon/apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="/showcase/favicon/favicon-32x32.png"/><link rel="icon" type="image/png" sizes="16x16" href="/showcase/favicon/favicon-16x16.png"/><link rel="manifest" href="/showcase/favicon/site.webmanifest"/><link rel="mask-icon" href="/showcase/favicon/safari-pinned-tab.svg" color="##5bbad5"/><link rel="shortcut icon" href="/showcase/favicon/favicon.ico"/><meta name="msapplication-TileColor" content="##5bbad5"/><meta name="msapplication-config" content="/showcase/favicon/browserconfig.xml"/><meta name="theme-color" content="#ffffff"/><title>Pseudobulbar Palsy Detection with Wav2Vec2 and OpenAI Whisper</title><meta name="twitter:card" content="summary"/><meta property="og:title" content="Pseudobulbar Palsy Detection with Wav2Vec2 and OpenAI 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Manga Recommendation</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Jenta Wonglertsakul<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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เรื่องที่ใกล้เคียงกับความต้องการมากที่สุด\n- เริ่มต้นเก็บข้อมูลจากการ scrape MyAnimeList.net และ anime-planet แต่ประสบปัญหา จึงลองใช้ชุดข้อมูล victorsoeiro/manga-manhwa-and-manhua-datasetจาก Kaggle แทน\n- สร้างชุดข้อมูล (คำสั่งค้นหา, คำอธิบายการ์ตูน) โดยการใช้ LLaMA2 สร้างคำสั่งขึ้นมาด้วย Prompt “[Given the description] Give me 5 natural language query which don't be too specific and not mention about manga name and character that will return a manga with the following description”\n- คำสั่งค้นหาที่ได้มา ยกตัวอย่างถ้าเป็น My Hero Academia โมเดล LLaMA2 จะแนะนำ “What is the name of a manga about a middle school student who wants to be a hero but doesn’t have any powers?”\n- ใช้ all-MiniLM-L6-v2 และ paraphrase-multilingual-mpnet-base-v2 ผ่าน SentenceTransformer เพื่อคำนวณความใกล้ของคำสั่งค้นหากับคำอธิบายการ์ตูน; ข้อดีของการเริ่มด้วย multilingual model คือสามารถค้นหาข้ามภาษาได้ แม้ชุดข้อมูลของเราจะเป็นภาษาอังกฤษล้วน เช่น “ขอการ์ตูนเด็กแว่นนักสืบ” ก็จะได้ Detective Conan\n- หลังการ finetune ทุกโมเดลมี top-k accuracy เพิ่มขึ้นประมาณ10% (top-1 75%, top-3 80%, top-5 85%); top-k accuracy คือโมเดลแนะนำถูกภายในเรื่องที่มั่นใจที่สุดกี่เรื่อง\n- ทำแบบทดสอบกับผู้ใช้จริงแล้วพบว่าแนะนำได้ตรงใจกว่า ChatGPT; เหตุผลคือ ChatGPT ไม่ได้ถูก finetune กับชุดข้อมูลเฉพาะทาง ทำให้จะแนะนำแต่การ์ตูนตลาด เช่น วันพีซ นารุโตะ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e ที่ผ่านมาตอนเริ่มเขียนโค้ดใหม่ก็ได้ไปเรียนที่สอนโค้ดที่หนึ่งพี่เจ้าของก็จะชอบให้งานเจน และบอกกับเจนว่าเจนเหมือนพี่ บางทีให้โจทย์โจทย์นึงมา พอลองตอบไปก็พบว่า แกจะชอบบอกว่า คำตอบของเจนเข้าใกล้ความถูกต้องแล้ว แต่เจนยังไม่ break through ไปถึงคำตอบซักทีเจนไม่ยอมวาปไปถึงคำตอบ หลังจากนั้นก็มีคำถามมากมายในหัวเจนว่า เราวาปได้หรอ ถ้าเรา break through แล้วจะได้อะไร จะ level up หรอ เขาจะชอบให้เจน break limit ทำอะไรให้เกิน limit ตัวเอง ตอนนั้นเจนคงว่างเลยทำตามไป ตอนนั้นมีฝืนร่างกายบ้าง ตอนนั้นเชื่อคนง่าย ไม่มั่นใจในตัวเอง แต่ผ่านไปซักพักเจนมั่นใจในตัวเอง เขาบอกว่าเป็นการมั่นใจที่ผิดๆ แถมพี่ในที่นั้นที่เคยสอนเจน ก็ชอบดูถูกเจน เลยคิดว่าถ้าตัวเองเก่งขึ้น พัฒนาตัวเองได้มากขึ้น โดยไม่ฝืนร่างกาย ทำอะไรที่เป็นรูปธรรมที่มีประโยชน์ และพวกเขาได้ใช้และรู้ว่ามาจากเจน มันคงเป็นความรู้สึกดีมากๆ ที่ทำให้พวกเขาได้รู้ว่าเจนไม่ใช่คนชักจูงง่าย ไม่มั่นใจในตัวเอง ไม่ใช่เหมือนที่เขาดูถูกไว้ ทำประโยชน์ให้หลายๆคนได้ อีกอย่างคือเวลาเราทำอะไรที่เราชอบ แล้วมันมีประโยชน์ต่อคนอื่น ที่บ้านบางครั้งก็ชอบบ่นว่าเจนได้เริ่มเขียนโค้ดตอนช่วงโควิด ตอนนั้นเขียนเพราะไม่มีอะไรทำ ทำไปทำมา ก็ได้มาสอนที่ hamster hub เรื่อง basic python, oop จากนั้นก็ได้ลองคิดคอร์ส math with python ep.2, 4(logic, probablity) ตอนนั้นสนุกกับการเขียน python มากๆ หลังจากนั้นก็ต้องไปโรงเรียนซึ่งต้องอยู่หอ ทำให้ตัดสินใจพักงานสอน หลังจากนั้นไม่นานก็ทำสัมมนาที่โรงเรียน กับโครงงานเรื่อง stock portfolio optimization ทำให้เจนกลับมาเขียนโค้ดจริงจังอีกครั้ง ก่อนหน้านี้ก็มีเขียนบ้าง แต่ไม่ได้จริงจังมาก เริ่มมาศึกษา ai และได้เข้าร่วม cai hackathon : ได้ที่ 1 มา จากการทำ ai เรื่อง ai for mental health https://www.cpall.co.th/news/csr/creative-ai-club-hackathon เป็นจุดเปลี่ยนที่สำคัญที่ทำให้รู้สึกว่า เราน่าจะคิดอะไรที่เป็นประโยชน์ต่อคนอื่นได้ เลยลองสมัคร caic ซึ่งตอนนั้นได้รับโจทย์ ai เพื่อการตรวจสอบมาตราฐานของสมอบก ตอนนั้นเครียดมากเพราะมีเข้าค่าย สอวน.คอมพิวเตอร์ซ้อน แถมเพื่อนร่วมทีมเทงานไม่ค่อยช่วย เลยต้องเอามาทำ แต่ทุกอย่างก็ผ่านไปได้ ติดสอวน.รอบ 2 แต่ไม่ได้รางวัลอะไรจาก caic แต่ตรงนั้นทำให้รู้สึกว่าเราน่าจะลองทำ ai จริงจัง เพื่อช่วยคนอื่นซักทีนะ เพราะตอนได้สอนแล้วเห็นคนอื่นเข้าใจ\n","date":"31-7-24","title":"Manga Recommendation","builder":"Jenta Wonglertsakul","builder_info":"มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร","thumbnail":"/images/2023/82/01.jpg","links":{"github":"https://github.com/jjentaa/manga-recommendation","facebook":"https://www.facebook.com/aibuildersx/posts/pfbid0FHypCZy4s5ACv9WqSdxx6v9HtbVjZ2yhjuhAfcVCzf2hXCd5sc7285o2tx8iZ5Sol","blog":"https://medium.com/@madness_/manga-recommendation-️-a8147d933c51"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2023","id":"82-manga-recommendation"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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1v60ess">.css-1v60ess{display:-webkit-inline-box;display:-webkit-inline-flex;display:-ms-inline-flexbox;display:inline-flex;-webkit-appearance:none;-moz-appearance:none;-ms-appearance:none;appearance:none;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;position:absolute;white-space:nowrap;vertical-align:middle;outline:2px solid 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Manga Recommendation</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Jenta Wonglertsakul<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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เรื่องที่ใกล้เคียงกับความต้องการมากที่สุด\n- เริ่มต้นเก็บข้อมูลจากการ scrape MyAnimeList.net และ anime-planet แต่ประสบปัญหา จึงลองใช้ชุดข้อมูล victorsoeiro/manga-manhwa-and-manhua-datasetจาก Kaggle แทน\n- สร้างชุดข้อมูล (คำสั่งค้นหา, คำอธิบายการ์ตูน) โดยการใช้ LLaMA2 สร้างคำสั่งขึ้นมาด้วย Prompt “[Given the description] Give me 5 natural language query which don't be too specific and not mention about manga name and character that will return a manga with the following description”\n- คำสั่งค้นหาที่ได้มา ยกตัวอย่างถ้าเป็น My Hero Academia โมเดล LLaMA2 จะแนะนำ “What is the name of a manga about a middle school student who wants to be a hero but doesn’t have any powers?”\n- ใช้ all-MiniLM-L6-v2 และ paraphrase-multilingual-mpnet-base-v2 ผ่าน SentenceTransformer เพื่อคำนวณความใกล้ของคำสั่งค้นหากับคำอธิบายการ์ตูน; ข้อดีของการเริ่มด้วย multilingual model คือสามารถค้นหาข้ามภาษาได้ แม้ชุดข้อมูลของเราจะเป็นภาษาอังกฤษล้วน เช่น “ขอการ์ตูนเด็กแว่นนักสืบ” ก็จะได้ Detective Conan\n- หลังการ finetune ทุกโมเดลมี top-k accuracy เพิ่มขึ้นประมาณ10% (top-1 75%, top-3 80%, top-5 85%); top-k accuracy คือโมเดลแนะนำถูกภายในเรื่องที่มั่นใจที่สุดกี่เรื่อง\n- ทำแบบทดสอบกับผู้ใช้จริงแล้วพบว่าแนะนำได้ตรงใจกว่า ChatGPT; เหตุผลคือ ChatGPT ไม่ได้ถูก finetune กับชุดข้อมูลเฉพาะทาง ทำให้จะแนะนำแต่การ์ตูนตลาด เช่น วันพีซ นารุโตะ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e ที่ผ่านมาตอนเริ่มเขียนโค้ดใหม่ก็ได้ไปเรียนที่สอนโค้ดที่หนึ่งพี่เจ้าของก็จะชอบให้งานเจน และบอกกับเจนว่าเจนเหมือนพี่ บางทีให้โจทย์โจทย์นึงมา พอลองตอบไปก็พบว่า แกจะชอบบอกว่า คำตอบของเจนเข้าใกล้ความถูกต้องแล้ว แต่เจนยังไม่ break through ไปถึงคำตอบซักทีเจนไม่ยอมวาปไปถึงคำตอบ หลังจากนั้นก็มีคำถามมากมายในหัวเจนว่า เราวาปได้หรอ ถ้าเรา break through แล้วจะได้อะไร จะ level up หรอ เขาจะชอบให้เจน break limit ทำอะไรให้เกิน limit ตัวเอง ตอนนั้นเจนคงว่างเลยทำตามไป ตอนนั้นมีฝืนร่างกายบ้าง ตอนนั้นเชื่อคนง่าย ไม่มั่นใจในตัวเอง แต่ผ่านไปซักพักเจนมั่นใจในตัวเอง เขาบอกว่าเป็นการมั่นใจที่ผิดๆ แถมพี่ในที่นั้นที่เคยสอนเจน ก็ชอบดูถูกเจน เลยคิดว่าถ้าตัวเองเก่งขึ้น พัฒนาตัวเองได้มากขึ้น โดยไม่ฝืนร่างกาย ทำอะไรที่เป็นรูปธรรมที่มีประโยชน์ และพวกเขาได้ใช้และรู้ว่ามาจากเจน มันคงเป็นความรู้สึกดีมากๆ ที่ทำให้พวกเขาได้รู้ว่าเจนไม่ใช่คนชักจูงง่าย ไม่มั่นใจในตัวเอง ไม่ใช่เหมือนที่เขาดูถูกไว้ ทำประโยชน์ให้หลายๆคนได้ อีกอย่างคือเวลาเราทำอะไรที่เราชอบ แล้วมันมีประโยชน์ต่อคนอื่น ที่บ้านบางครั้งก็ชอบบ่นว่าเจนได้เริ่มเขียนโค้ดตอนช่วงโควิด ตอนนั้นเขียนเพราะไม่มีอะไรทำ ทำไปทำมา ก็ได้มาสอนที่ hamster hub เรื่อง basic python, oop จากนั้นก็ได้ลองคิดคอร์ส math with python ep.2, 4(logic, probablity) ตอนนั้นสนุกกับการเขียน python มากๆ หลังจากนั้นก็ต้องไปโรงเรียนซึ่งต้องอยู่หอ ทำให้ตัดสินใจพักงานสอน หลังจากนั้นไม่นานก็ทำสัมมนาที่โรงเรียน กับโครงงานเรื่อง stock portfolio optimization ทำให้เจนกลับมาเขียนโค้ดจริงจังอีกครั้ง ก่อนหน้านี้ก็มีเขียนบ้าง แต่ไม่ได้จริงจังมาก เริ่มมาศึกษา ai และได้เข้าร่วม cai hackathon : ได้ที่ 1 มา จากการทำ ai เรื่อง ai for mental health https://www.cpall.co.th/news/csr/creative-ai-club-hackathon เป็นจุดเปลี่ยนที่สำคัญที่ทำให้รู้สึกว่า เราน่าจะคิดอะไรที่เป็นประโยชน์ต่อคนอื่นได้ เลยลองสมัคร caic ซึ่งตอนนั้นได้รับโจทย์ ai เพื่อการตรวจสอบมาตราฐานของสมอบก ตอนนั้นเครียดมากเพราะมีเข้าค่าย สอวน.คอมพิวเตอร์ซ้อน แถมเพื่อนร่วมทีมเทงานไม่ค่อยช่วย เลยต้องเอามาทำ แต่ทุกอย่างก็ผ่านไปได้ ติดสอวน.รอบ 2 แต่ไม่ได้รางวัลอะไรจาก caic แต่ตรงนั้นทำให้รู้สึกว่าเราน่าจะลองทำ ai จริงจัง เพื่อช่วยคนอื่นซักทีนะ เพราะตอนได้สอนแล้วเห็นคนอื่นเข้าใจ\n","date":"31-7-24","title":"Manga Recommendation","builder":"Jenta Wonglertsakul","builder_info":"มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร","thumbnail":"/images/2023/82/01.jpg","links":{"github":"https://github.com/jjentaa/manga-recommendation","facebook":"https://www.facebook.com/aibuildersx/posts/pfbid0FHypCZy4s5ACv9WqSdxx6v9HtbVjZ2yhjuhAfcVCzf2hXCd5sc7285o2tx8iZ5Sol","blog":"https://medium.com/@madness_/manga-recommendation-️-a8147d933c51"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2023","id":"82-manga-recommendation"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">WoodSight</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Chetphisuth Tongpa<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Dog Breed Classification</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Pakin Olanraktham<!-- --> • <!-- -->มัธยมศึกษาปีที่ 1.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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fox_ears, serafuku, braid, animal_ear_fluff, white_dress”\n- เก็บข้อมูล tags จาก Danbooru2021 และเปลี่ยนข้อมูล tag เป็นคำอธิบายภาษาธรรมชาติด้วย gpt-3.5-turbo เป็น training set จำนวน 20k คู่คำอธิบายภาษาธรรมชาติ-tagจากทั้งหมด 5 ล้านคู่\n- ทำความสะอาดข้อมูลโดย 1) ลบรูปที่ถูกลบหรือแบนเพื่อรักษามาตรฐานจริยธรรม2) ใช้ข้อมูลจาก 2016-2021 เพื่อให้ได้ความสดใหม่ 3) ใช้เฉพาะรูปที่มีจำนวน tag เกิน 15 อันเพื่อให้ chatgpt สามารถสร้างคำบรรยายภาษาธรรมชาติได้อย่างเหมาะสม\n- เพื่อให้ได้ชุดข้อมูลในการเทรนที่ดีที่สุด ให้ prompt กับ chatgpt ว่าให้สร้างคำบรรยายจาก tag ที่เห็นเท่านั้นโดยไม่มีการคาดเดาเองเพิ่มเติม,อธิบายให้ chatgpt ฟังว่า tag แต่ละอันเกี่ยวกับผู้วาด, ตัวละคร, ลิขสิทธิ์, ที่มา, หรือคำบรรยายทั่วไป\n- เลือกใช้เฉพาะ tag ที่ถูกใช้ในรูป 500 รูปขึ้นไปเพื่อไม่ให้เจอ tag ที่เฉพาะเจาะจงเกินไป\n- ใช้ recall เป็นตัวชี้วัดหลักเนื่องจากสิ่งที่สำคัญคือให้โมเดลสร้าง tag ที่จำเป็นเพื่อให้ได้รูปตามที่ผู้ใช้ต้องการ; หากโมเดลแนะนำ tag ที่ไม่ต้องการออกมาบ้างผู้ใช้ยังสามารถลบออกได้เอง recall จึงสำคัญกว่า precision\n- Baseline ผลการทำงานเทียบกับมนุษย์ (ผู้สร้างโมเดล)ลงทุนเขียนคำบรรยายภาษาธรรมชาติเองใน 30 คู่จาก 150 คู่ใน test set ได้ recall 0.456, ใช้ booru tag autocomplete expansion ได้ recall 0.414\n- ทดสอบ finetune โมเดลหลายประเภทได้แก่ Cerebras-GPT-1.3B (recall = 0.372), DeBERTa v2 (ลองเปลี่ยนจากปัญหา text generation เป็น multi-label classification แต่ได้ผลไม่ดี),Llama-7B (0.539; ดีกว่ามนุษย์ถึง18%!!)\n- ทำ quantization เพื่อนำโมเดลมาใช้ในเครื่องสำหรับผู้บริโภคด้วยllama-cpp; หลังจากลดขนาดโมเดลแล้ว recall ดันดีขึ้น (อาจจะเพราะ regularization)เป็น recall 0.561!!!\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e i still vividly recall the day when i first discovered the world of artificial intelligence. it was just like any other evening spent browsing youtube when a video by two minute papers caught my attention. I clicked on it, expecting nothing more than a quick distraction, but what i found was so much more. it was a digestible explanation of a paper titled “emergent tool use from multi-agent interaction” where ai agents learned increasingly complex strategies in a simple hide-and-seek environment. i was awed when the ai agents started exploiting bugs in the physics of the simulation to gain an edge as if it was a human speedrunner.\u0026nbsp; that video sparked something within me, and i was prompted to delve deeper, binging on videos about everything from self-driving cars to deepfake detectors. it became clear that these technologies were not justi am a self motivated student who is eager to go beyond requirements and strive for excellence. studying at a stem school, i have always challenged myself with rigorous courses. like ap calculus bc, advanced stem with arduino, and ap computer science, while still consistently maintaining straight-as my fascination with ai has also led me to extracurricularstudy where i have gained relevant skills. i started out with a python bootcamp on udemy, andhave since applied my skills to automate daily tasks, writing scripts for signing into wifi, for instance. additionally, i completed advent of code programming challenge using python, which involved 25 days of increasingly difficult puzzles that pushed my knowledge and application of algorithms to their limits. having familiarized myself with python, i continued with ai courses. i completed harvard’s cs50\n    ","date":"31-7-24","title":"Text2Tags","builder":"Pantai Suyasri","builder_info":"มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร","thumbnail":"/images/2023/94/01.jpg","links":{"github":"https://github.com/DatboiiPuntai/text2tags-lib","facebook":"https://www.facebook.com/aibuildersx/posts/pfbid0iW4oj7tRobENdSPH8ALTBJEG5TAqZQU2kmu36U2DndpoPugC2VR2d8V9fCz7ExqDl","blog":"https://medium.com/@pantaisuyasri/extracting-danbooru-tags-from-text-9b820478a7d8"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2023","id":"94-text2tags"},"buildId":"P1wceHoGgr6TnuCfa06o0","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Text2Tags</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Pantai Suyasri<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a></div></div></div></div><span></span></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"postData":{"id":"94-text2tags","content":"\n![image](/images/2023/94/01.jpg)\n\n- โมเดลเปลี่ยนภาษาธรรมชาติเป็นภาษา prompt เพื่อสร้างรูปภาพด้วย Stable Diffusion; เนื่องจากโมเดลสร้างรูปภาพตามท้องตลาดถูกฝึกมา (อย่างไม่ถูกลิขสิทธิ์) จากข้อมูล tag และรูปภาพในเว็บฝากรูป โมเดลจึงเข้าใจคำสั่งภาษาธรรมชาติ เช่น “Shirakami Fubuki in a white sailor school uniform” ได้ยากกว่าคำสั่งในรูปแบบเดียวกับ tag เช่น “1girl, animal_ears, aqua_eyes, fox_girl, shirakami_fubuki, hololive, virtual_youtuber, fox_ears, serafuku, braid, animal_ear_fluff, white_dress”\n- เก็บข้อมูล tags จาก Danbooru2021 และเปลี่ยนข้อมูล tag เป็นคำอธิบายภาษาธรรมชาติด้วย gpt-3.5-turbo เป็น training set จำนวน 20k คู่คำอธิบายภาษาธรรมชาติ-tagจากทั้งหมด 5 ล้านคู่\n- ทำความสะอาดข้อมูลโดย 1) ลบรูปที่ถูกลบหรือแบนเพื่อรักษามาตรฐานจริยธรรม2) ใช้ข้อมูลจาก 2016-2021 เพื่อให้ได้ความสดใหม่ 3) ใช้เฉพาะรูปที่มีจำนวน tag เกิน 15 อันเพื่อให้ chatgpt สามารถสร้างคำบรรยายภาษาธรรมชาติได้อย่างเหมาะสม\n- เพื่อให้ได้ชุดข้อมูลในการเทรนที่ดีที่สุด ให้ prompt กับ chatgpt ว่าให้สร้างคำบรรยายจาก tag ที่เห็นเท่านั้นโดยไม่มีการคาดเดาเองเพิ่มเติม,อธิบายให้ chatgpt ฟังว่า tag แต่ละอันเกี่ยวกับผู้วาด, ตัวละคร, ลิขสิทธิ์, ที่มา, หรือคำบรรยายทั่วไป\n- เลือกใช้เฉพาะ tag ที่ถูกใช้ในรูป 500 รูปขึ้นไปเพื่อไม่ให้เจอ tag ที่เฉพาะเจาะจงเกินไป\n- ใช้ recall เป็นตัวชี้วัดหลักเนื่องจากสิ่งที่สำคัญคือให้โมเดลสร้าง tag ที่จำเป็นเพื่อให้ได้รูปตามที่ผู้ใช้ต้องการ; หากโมเดลแนะนำ tag ที่ไม่ต้องการออกมาบ้างผู้ใช้ยังสามารถลบออกได้เอง recall จึงสำคัญกว่า precision\n- Baseline ผลการทำงานเทียบกับมนุษย์ (ผู้สร้างโมเดล)ลงทุนเขียนคำบรรยายภาษาธรรมชาติเองใน 30 คู่จาก 150 คู่ใน test set ได้ recall 0.456, ใช้ booru tag autocomplete expansion ได้ recall 0.414\n- ทดสอบ finetune โมเดลหลายประเภทได้แก่ Cerebras-GPT-1.3B (recall = 0.372), DeBERTa v2 (ลองเปลี่ยนจากปัญหา text generation เป็น multi-label classification แต่ได้ผลไม่ดี),Llama-7B (0.539; ดีกว่ามนุษย์ถึง18%!!)\n- ทำ quantization เพื่อนำโมเดลมาใช้ในเครื่องสำหรับผู้บริโภคด้วยllama-cpp; หลังจากลดขนาดโมเดลแล้ว recall ดันดีขึ้น (อาจจะเพราะ regularization)เป็น recall 0.561!!!\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e i still vividly recall the day when i first discovered the world of artificial intelligence. it was just like any other evening spent browsing youtube when a video by two minute papers caught my attention. I clicked on it, expecting nothing more than a quick distraction, but what i found was so much more. it was a digestible explanation of a paper titled “emergent tool use from multi-agent interaction” where ai agents learned increasingly complex strategies in a simple hide-and-seek environment. i was awed when the ai agents started exploiting bugs in the physics of the simulation to gain an edge as if it was a human speedrunner.\u0026nbsp; that video sparked something within me, and i was prompted to delve deeper, binging on videos about everything from self-driving cars to deepfake detectors. it became clear that these technologies were not justi am a self motivated student who is eager to go beyond requirements and strive for excellence. studying at a stem school, i have always challenged myself with rigorous courses. like ap calculus bc, advanced stem with arduino, and ap computer science, while still consistently maintaining straight-as my fascination with ai has also led me to extracurricularstudy where i have gained relevant skills. i started out with a python bootcamp on udemy, andhave since applied my skills to automate daily tasks, writing scripts for signing into wifi, for instance. additionally, i completed advent of code programming challenge using python, which involved 25 days of increasingly difficult puzzles that pushed my knowledge and application of algorithms to their limits. having familiarized myself with python, i continued with ai courses. i completed harvard’s cs50\n    ","date":"31-7-24","title":"Text2Tags","builder":"Pantai Suyasri","builder_info":"มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร","thumbnail":"/images/2023/94/01.jpg","links":{"github":"https://github.com/DatboiiPuntai/text2tags-lib","facebook":"https://www.facebook.com/aibuildersx/posts/pfbid0iW4oj7tRobENdSPH8ALTBJEG5TAqZQU2kmu36U2DndpoPugC2VR2d8V9fCz7ExqDl","blog":"https://medium.com/@pantaisuyasri/extracting-danbooru-tags-from-text-9b820478a7d8"}}},"__N_SSG":true},"page":"/[year]/[id]","query":{"year":"2023","id":"94-text2tags"},"buildId":"8Svqkuv7Is15opn2UcCBZ","assetPrefix":"/showcase","isFallback":false,"gsp":true,"scriptLoader":[]}</script></body></html>
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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">CATsification</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Pawinthawat Chandravat<!-- --> • <!-- -->มัธยมศึกษาปีที่ 3.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">AI FallingAsleepDriving (AI ตรวจสอบผู้ขับขี่หลับใน)</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Puratsakorn Kietnonthapat<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- สงขลา</h4><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 3jcdv2">.css-3jcdv2{text-align:center;margin-bottom:var(--chakra-space-6);}</style><div class="css-3jcdv2"><style data-emotion="css 1pbpsj9">.css-1pbpsj9{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-4xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}@media screen and (min-width: 48em){.css-1pbpsj9{font-size:var(--chakra-fontSizes-5xl);line-height:1;}}</style><h1 class="chakra-heading css-1pbpsj9">Phish-Off</h1><style data-emotion="css qmggpo">.css-qmggpo{font-family:var(--chakra-fonts-heading);font-weight:var(--chakra-fontWeights-bold);font-size:var(--chakra-fontSizes-xl);line-height:1.2;margin-bottom:var(--chakra-space-6);}</style><h4 class="chakra-heading css-qmggpo">โดย <!-- -->Plengpin Tongdon-Ngao<!-- --> • <!-- -->มัธยมศึกษาปีที่ 5.0 -- กรุงเทพมหานคร</h4><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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dataset ของโมเดลที่ทำ และสามารถวัดผลได้อย่างชัดเจนที่สุดโดยไม่มี bias ของมนุษย์เข้ามาเจือปน\n- Dataset ที่ใช้ มาจากฐานข้อมูลงานศิลปะจากศิลปินชั้นครูจากประเทศฝั่งตะวันตก\n- Preprocessing ด้วยการครอปรูปในการเทรนให้มีขนาดท่ากัน แต่ยังคงรายละเอียดให้ครบถ้วนที่สุดเพื่อไม่ให้ส่งผลต่อประสิทธิภาพของโมเดล และเพิ่มความหลากหลายของ training set ด้วยการ augmentation โดยเลือกวิธีไม่ให้กระทบกับคุณภาพของ training images ที่คัดกรองมาแล้วอีกเช่นกัน\n- Fine-Tune แบบสำเร็จรูปด้วยคำสั่ง learn.fine_tune\n- Evaluate โดยการเทียบกับผลลัพธ์ที่ได้จากโปรแกรมแบบ rule-based ที่ทำเอาไว้ก่อนหน้า และกับความสามารถของคนที่มีความรู้ด้านศิลปะที่ใช้แบบสอบถามในการประเมิน (ในส่วนนี้เนื่องจากยังอยู่ในระหว่างการพัฒนา คาดว่าจะได้ประสิทธิภาพไม่สูงไปกว่า rule-based model แต่จะสูงกว่าผลที่วัดจากการประเมินด้วยสายตาคน)\n- Suggestion หากพบช่องโหว่ในกฎที่ใช้ในการเทรน อาจต้องมีการปรับปรุงกฎให้เลียนแบบทฤษฎีได้อย่างใกล้เคียงมากขึ้น และโมเดลนี้ หากมีฐานข้อมูลจำนวนมากพอ อาจให้ผลลัพธ์ที่ถูกต้องได้ถึง 100% แต่โดยพื้นฐานแล้ว ศาสตร์เกี่ยวกับความสัมพันธ์ระหว่างสีเป็นสิ่งที่มีความคลุมเครืออยู่ในตัวของมันเอง เพราะฉะนั้นหากต้องการพัฒนาโมเดลต่อ อาจต้องมีการ discuss กับผู้ที่มีความเชี่ยวชาญเฉพาะด้านศิลปะ เพื่อหา criteria ฉบับปรับปรุงที่เหมาะแก่การนำไปใช้ที่สุด\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n\u003e อยากมีความรู้เกี่ยวกับการสร้างปัญญาประดิษฐ์เพื่อที่จะทำประโยชน์ให้แก่สังคมที่ตัวเองอยู่ และนำไปใช้งานในสายอาชีพที่เกี่ยวข้องกับเทคโนโลยีและสาขาอื่น ๆ ที่สนใจในอนาคตค่ะ อยากได้สิ่งที่จำเป็นในการสร้างอนาคตที่เอื้อต่อการอยู่ร่วมกันของมนุษย์และปัญญาประดิษฐ์ในสายงานต่าง ๆ และในชีวิตประจำวัน โดยไม่ให้เกิดการเปลี่ยนแปลงขนาดใหญ่ในเวลาสั้น ๆ ซึ่งอาจส่งผลต่อชีวิตและความเป็นอยู่ของคนจำนวนมาก ซึ่งเป็นสิ่งที่สามารถพบเห็นได้ในทุกวันนี้ว่ามีคนจำนวนมากสูญเสียงานเนื่องจากการแทนที่ของ ai ในสายงานต่าง ๆ โดยที่มาของความตั้งใจนี้มาจากการที่ดิฉันได้มองเห็นทั้งข้อดีและข้อเสียของการนำ ai มาใช้งานในชีวิตประจำวัน 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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property="og:description" content="ณัฐวีณ์ สุนิตย์สกุล( ตัง) • ดรุณสิกขาลัย (โครงการ kosen kmutt) / กรุงเทพมหานคร"/><meta property="og:image" content="https://ai-builders.github.io/showcase/images/2024/3/01.png"/><meta property="og:site_name" content="AI Builders Showcase"/><meta name="next-head-count" content="17"/><link rel="preload" href="/showcase/_next/static/css/f9f072bebc05078a.css" as="style"/><link rel="stylesheet" href="/showcase/_next/static/css/f9f072bebc05078a.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/showcase/_next/static/chunks/polyfills-5cd94c89d3acac5f.js"></script><script src="/showcase/_next/static/chunks/webpack-74b12628e711d77e.js" defer=""></script><script src="/showcase/_next/static/chunks/framework-5f4595e5518b5600.js" defer=""></script><script src="/showcase/_next/static/chunks/main-e95b58999d220b83.js" defer=""></script><script src="/showcase/_next/static/chunks/pages/_app-cafc0401ce7959b1.js" 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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type="button" class="chakra-button css-1v60ess">เกี่ยวกับเรา</button></div></div></div><style data-emotion="css jf7n8r">.css-jf7n8r{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-xl);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-jf7n8r"><style data-emotion="css h96cfs">.css-h96cfs{padding-top:var(--chakra-space-6);padding-bottom:var(--chakra-space-12);}</style><div class="css-h96cfs"><style data-emotion="css 1xo1xlh">.css-1xo1xlh{width:100%;-webkit-margin-start:auto;margin-inline-start:auto;-webkit-margin-end:auto;margin-inline-end:auto;max-width:var(--chakra-sizes-container-lg);-webkit-padding-start:1rem;padding-inline-start:1rem;-webkit-padding-end:1rem;padding-inline-end:1rem;}</style><div class="chakra-container css-1xo1xlh"><style data-emotion="css 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/001-foody-dudy.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/001-foody-dudy.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/001-foody-dudy.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/001-foody-dudy.json
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle.json
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/003-Lalita-Chinese-Thai-Machine-Translation.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/003-Lalita-Chinese-Thai-Machine-Translation.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/003-Lalita-Chinese-Thai-Machine-Translation.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/003-Lalita-Chinese-Thai-Machine-Translation.json
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/004-\340\271\201\340\270\231\340\270\260\340\270\231\340\270\263\340\270\243\340\270\262\340\270\204\340\270\262\340\270\243\340\270\271\340\270\233\340\270\204\340\270\255\340\270\241\340\270\241\340\270\264\340\270\212\340\270\212\340\270\261\340\270\231\340\270\255\340\270\231\340\270\264\340\271\200\340\270\241\340\270\260\340\270\224\340\271\211\340\270\247\340\270\242-machine-learning-\340\271\202\340\270\224\340\270\242-fastai.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/004-\340\271\201\340\270\231\340\270\260\340\270\231\340\270\263\340\270\243\340\270\262\340\270\204\340\270\262\340\270\243\340\270\271\340\270\233\340\270\204\340\270\255\340\270\241\340\270\241\340\270\264\340\270\212\340\270\212\340\270\261\340\270\231\340\270\255\340\270\231\340\270\264\340\271\200\340\270\241\340\270\260\340\270\224\340\271\211\340\270\247\340\270\242-machine-learning-\340\271\202\340\270\224\340\270\242-fastai.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/004-\340\271\201\340\270\231\340\270\260\340\270\231\340\270\263\340\270\243\340\270\262\340\270\204\340\270\262\340\270\243\340\270\271\340\270\233\340\270\204\340\270\255\340\270\241\340\270\241\340\270\264\340\270\212\340\270\212\340\270\261\340\270\231\340\270\255\340\270\231\340\270\264\340\271\200\340\270\241\340\270\260\340\270\224\340\271\211\340\270\247\340\270\242-machine-learning-\340\271\202\340\270\224\340\270\242-fastai.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/004-\340\271\201\340\270\231\340\270\260\340\270\231\340\270\263\340\270\243\340\270\262\340\270\204\340\270\262\340\270\243\340\270\271\340\270\233\340\270\204\340\270\255\340\270\241\340\270\241\340\270\264\340\270\212\340\270\212\340\270\261\340\270\231\340\270\255\340\270\231\340\270\264\340\271\200\340\270\241\340\270\260\340\270\224\340\271\211\340\270\247\340\270\242-machine-learning-\340\271\202\340\270\224\340\270\242-fastai.json"
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/005-Thai-Text-to-Speech-with-Tacotron.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/005-Thai-Text-to-Speech-with-Tacotron.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/005-Thai-Text-to-Speech-with-Tacotron.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/005-Thai-Text-to-Speech-with-Tacotron.json
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/006-Salmon-Classifier-\340\271\200\340\270\243\340\270\267\340\271\210\340\270\255\340\270\207\340\270\247\340\270\270\340\271\210\340\270\231\340\271\206\340\270\202\340\270\255\340\270\207\340\270\233\340\270\245\340\270\262\340\271\201\340\270\213\340\270\245\340\270\241\340\270\255\340\270\231.json"
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/007-Thai-Music-Generation-with-VAE.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/007-Thai-Music-Generation-with-VAE.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/007-Thai-Music-Generation-with-VAE.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/007-Thai-Music-Generation-with-VAE.json
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/008-Itinerary-Creator-\340\271\202\340\270\233\340\270\243\340\271\201\340\270\201\340\270\243\340\270\241\340\270\212\340\271\210\340\270\247\340\270\242\340\270\247\340\270\262\340\270\207\340\271\201\340\270\234\340\270\231\340\270\201\340\270\262\340\270\243\340\271\200\340\270\227\340\270\265\340\271\210\340\270\242\340\270\247\340\271\203\340\270\253\340\271\211\340\271\203\340\270\201\340\270\245\340\271\211\340\271\200\340\270\204\340\270\265\340\270\242\340\270\207\340\270\201\340\270\261\340\270\232\340\270\204\340\270\247\340\270\262\340\270\241\340\270\212\340\270\255\340\270\232\340\270\202\340\270\255\340\270\207\340\271\200\340\270\243\340\270\262.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/008-Itinerary-Creator-\340\271\202\340\270\233\340\270\243\340\271\201\340\270\201\340\270\243\340\270\241\340\270\212\340\271\210\340\270\247\340\270\242\340\270\247\340\270\262\340\270\207\340\271\201\340\270\234\340\270\231\340\270\201\340\270\262\340\270\243\340\271\200\340\270\227\340\270\265\340\271\210\340\270\242\340\270\247\340\271\203\340\270\253\340\271\211\340\271\203\340\270\201\340\270\245\340\271\211\340\271\200\340\270\204\340\270\265\340\270\242\340\270\207\340\270\201\340\270\261\340\270\232\340\270\204\340\270\247\340\270\262\340\270\241\340\270\212\340\270\255\340\270\232\340\270\202\340\270\255\340\270\207\340\271\200\340\270\243\340\270\262.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/008-Itinerary-Creator-\340\271\202\340\270\233\340\270\243\340\271\201\340\270\201\340\270\243\340\270\241\340\270\212\340\271\210\340\270\247\340\270\242\340\270\247\340\270\262\340\270\207\340\271\201\340\270\234\340\270\231\340\270\201\340\270\262\340\270\243\340\271\200\340\270\227\340\270\265\340\271\210\340\270\242\340\270\247\340\271\203\340\270\253\340\271\211\340\271\203\340\270\201\340\270\245\340\271\211\340\271\200\340\270\204\340\270\265\340\270\242\340\270\207\340\270\201\340\270\261\340\270\232\340\270\204\340\270\247\340\270\262\340\270\241\340\270\212\340\270\255\340\270\232\340\270\202\340\270\255\340\270\207\340\271\200\340\270\243\340\270\262.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/008-Itinerary-Creator-\340\271\202\340\270\233\340\270\243\340\271\201\340\270\201\340\270\243\340\270\241\340\270\212\340\271\210\340\270\247\340\270\242\340\270\247\340\270\262\340\270\207\340\271\201\340\270\234\340\270\231\340\270\201\340\270\262\340\270\243\340\271\200\340\270\227\340\270\265\340\271\210\340\270\242\340\270\247\340\271\203\340\270\253\340\271\211\340\271\203\340\270\201\340\270\245\340\271\211\340\271\200\340\270\204\340\270\265\340\270\242\340\270\207\340\270\201\340\270\261\340\270\232\340\270\204\340\270\247\340\270\262\340\270\241\340\270\212\340\270\255\340\270\232\340\270\202\340\270\255\340\270\207\340\271\200\340\270\243\340\270\262.json"
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/009-Finger-Movement-Classification-from-Electromyography.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/009-Finger-Movement-Classification-from-Electromyography.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/009-Finger-Movement-Classification-from-Electromyography.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/009-Finger-Movement-Classification-from-Electromyography.json
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/010-\340\270\201\340\270\262\340\270\243\340\270\243\340\270\271\340\271\211\340\270\210\340\270\263\340\270\255\340\270\262\340\270\243\340\270\241\340\270\223\340\271\214\340\271\200\340\270\252\340\270\265\340\270\242\340\270\207\340\270\236\340\270\271\340\270\224\340\270\224\340\271\211\340\270\247\340\270\242-ThaiserDataset.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/010-\340\270\201\340\270\262\340\270\243\340\270\243\340\270\271\340\271\211\340\270\210\340\270\263\340\270\255\340\270\262\340\270\243\340\270\241\340\270\223\340\271\214\340\271\200\340\270\252\340\270\265\340\270\242\340\270\207\340\270\236\340\270\271\340\270\224\340\270\224\340\271\211\340\270\247\340\270\242-ThaiserDataset.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/010-\340\270\201\340\270\262\340\270\243\340\270\243\340\270\271\340\271\211\340\270\210\340\270\263\340\270\255\340\270\262\340\270\243\340\270\241\340\270\223\340\271\214\340\271\200\340\270\252\340\270\265\340\270\242\340\270\207\340\270\236\340\270\271\340\270\224\340\270\224\340\271\211\340\270\247\340\270\242-ThaiserDataset.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/010-\340\270\201\340\270\262\340\270\243\340\270\243\340\270\271\340\271\211\340\270\210\340\270\263\340\270\255\340\270\262\340\270\243\340\270\241\340\270\223\340\271\214\340\271\200\340\270\252\340\270\265\340\270\242\340\270\207\340\270\236\340\270\271\340\270\224\340\270\224\340\271\211\340\270\247\340\270\242-ThaiserDataset.json"
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/011-\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\234\340\270\245\340\270\234\340\270\245\340\270\264\340\270\225\340\270\202\340\270\255\340\270\207\340\270\236\340\270\267\340\270\212\340\271\200\340\270\250\340\270\243\340\270\251\340\270\220\340\270\201\340\270\264\340\270\210-\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211\340\271\200\340\270\227\340\270\204\340\270\231\340\270\264\340\270\204-Machine-Learning.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/011-\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\234\340\270\245\340\270\234\340\270\245\340\270\264\340\270\225\340\270\202\340\270\255\340\270\207\340\270\236\340\270\267\340\270\212\340\271\200\340\270\250\340\270\243\340\270\251\340\270\220\340\270\201\340\270\264\340\270\210-\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211\340\271\200\340\270\227\340\270\204\340\270\231\340\270\264\340\270\204-Machine-Learning.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/011-\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\234\340\270\245\340\270\234\340\270\245\340\270\264\340\270\225\340\270\202\340\270\255\340\270\207\340\270\236\340\270\267\340\270\212\340\271\200\340\270\250\340\270\243\340\270\251\340\270\220\340\270\201\340\270\264\340\270\210-\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211\340\271\200\340\270\227\340\270\204\340\270\231\340\270\264\340\270\204-Machine-Learning.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/011-\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\234\340\270\245\340\270\234\340\270\245\340\270\264\340\270\225\340\270\202\340\270\255\340\270\207\340\270\236\340\270\267\340\270\212\340\271\200\340\270\250\340\270\243\340\270\251\340\270\220\340\270\201\340\270\264\340\270\210-\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211\340\271\200\340\270\227\340\270\204\340\270\231\340\270\264\340\270\204-Machine-Learning.json"
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/012--Visual Hand-Command-things-with-your-hand-DIY.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/012--Visual Hand-Command-things-with-your-hand-DIY.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/012--Visual Hand-Command-things-with-your-hand-DIY.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/012--Visual Hand-Command-things-with-your-hand-DIY.json
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/013-Making-AI-Model-for-Reversi-Game.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/013-Making-AI-Model-for-Reversi-Game.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/013-Making-AI-Model-for-Reversi-Game.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/013-Making-AI-Model-for-Reversi-Game.json
diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/014-Machine-Learning-for-Alzheimer's-Detection-from-MRI-Images.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/014-Machine-Learning-for-Alzheimer's-Detection-from-MRI-Images.json
similarity index 100%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/2021/014-Machine-Learning-for-Alzheimer's-Detection-from-MRI-Images.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/2021/014-Machine-Learning-for-Alzheimer's-Detection-from-MRI-Images.json
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/015-Image-Captioning-in-Thai-AI-\340\270\212\340\271\210\340\270\247\340\270\242\340\270\234\340\270\271\340\271\211\340\270\236\340\270\264\340\270\201\340\270\262\340\270\243\340\270\227\340\270\262\340\270\207\340\270\252\340\270\262\340\270\242\340\270\225\340\270\262.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/015-Image-Captioning-in-Thai-AI-\340\270\212\340\271\210\340\270\247\340\270\242\340\270\234\340\270\271\340\271\211\340\270\236\340\270\264\340\270\201\340\270\262\340\270\243\340\270\227\340\270\262\340\270\207\340\270\252\340\270\262\340\270\242\340\270\225\340\270\262.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/015-Image-Captioning-in-Thai-AI-\340\270\212\340\271\210\340\270\247\340\270\242\340\270\234\340\270\271\340\271\211\340\270\236\340\270\264\340\270\201\340\270\262\340\270\243\340\270\227\340\270\262\340\270\207\340\270\252\340\270\262\340\270\242\340\270\225\340\270\262.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/015-Image-Captioning-in-Thai-AI-\340\270\212\340\271\210\340\270\247\340\270\242\340\270\234\340\270\271\340\271\211\340\270\236\340\270\264\340\270\201\340\270\262\340\270\243\340\270\227\340\270\262\340\270\207\340\270\252\340\270\262\340\270\242\340\270\225\340\270\262.json"
diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/016-STONK-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\243\340\270\262\340\270\204\340\270\262\340\270\253\340\270\270\340\271\211\340\270\231\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211-machine-learning.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/016-STONK-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\243\340\270\262\340\270\204\340\270\262\340\270\253\340\270\270\340\271\211\340\270\231\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211-machine-learning.json"
similarity index 100%
rename from "_next/data/P1wceHoGgr6TnuCfa06o0/2021/016-STONK-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\243\340\270\262\340\270\204\340\270\262\340\270\253\340\270\270\340\271\211\340\270\231\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211-machine-learning.json"
rename to "_next/data/8Svqkuv7Is15opn2UcCBZ/2021/016-STONK-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\243\340\270\262\340\270\204\340\270\262\340\270\253\340\270\270\340\271\211\340\270\231\340\271\202\340\270\224\340\270\242\340\271\203\340\270\212\340\271\211-machine-learning.json"
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/019-\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\234\340\270\245\340\270\232\340\270\255\340\270\245\340\270\242\340\270\261\340\270\207\340\271\204\340\270\207\340\271\203\340\270\253\340\271\211\340\271\201\340\270\241\340\271\210\340\270\231\340\270\213\340\270\260\340\270\242\340\270\264\340\271\210\340\270\207\340\270\201\340\270\247\340\271\210\340\270\262\340\270\253\340\270\241\340\270\266\340\270\201\340\270\236\340\270\255\340\270\245.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/019-\340\270\227\340\270\263\340\270\231\340\270\262\340\270\242\340\270\234\340\270\245\340\270\232\340\270\255\340\270\245\340\270\242\340\270\261\340\270\207\340\271\204\340\270\207\340\271\203\340\270\253\340\271\211\340\271\201\340\270\241\340\271\210\340\270\231\340\270\213\340\270\260\340\270\242\340\270\264\340\271\210\340\270\207\340\270\201\340\270\247\340\271\210\340\270\262\340\270\253\340\270\241\340\270\266\340\270\201\340\270\236\340\270\255\340\270\245.json"
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2021/020-TH-National-Document-OCR-(THNDOCR).json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2021/020-TH-National-Document-OCR-(THNDOCR).json
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/AI-\340\271\201\340\270\242\340\270\201\340\271\201\340\270\242\340\270\260\340\271\201\340\270\241\340\270\207\340\270\224\340\270\262\340\270\210\340\270\262\340\270\231-\340\270\201\340\270\261\340\270\232-\340\271\201\340\270\241\340\270\207\340\270\224\340\270\262\340\270\226\340\271\211\340\270\247\340\270\242.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/AI-\340\271\201\340\270\242\340\270\201\340\271\201\340\270\242\340\270\260\340\271\201\340\270\241\340\270\207\340\270\224\340\270\262\340\270\210\340\270\262\340\270\231-\340\270\201\340\270\261\340\270\232-\340\271\201\340\270\241\340\270\207\340\270\224\340\270\262\340\270\226\340\271\211\340\270\247\340\270\242.json"
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/BACK-(Blind-All-Can-Know)---Action-Captioning-for-Blinds.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/BACK-(Blind-All-Can-Know)---Action-Captioning-for-Blinds.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Brain-Tumor-Segmentation-using-SegResNet.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Brain-Tumor-Segmentation-using-SegResNet.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Cactus-Classification-with-Fastai.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Cactus-Classification-with-Fastai.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Classical-Music-Generator.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Classical-Music-Generator.json
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Crossec--\340\270\243\340\270\260\340\270\232\340\270\232\340\270\252\340\271\210\340\270\207\340\271\200\340\270\252\340\270\243\340\270\264\340\270\241\340\270\201\340\270\262\340\270\243\340\270\227\340\270\263\340\270\233\340\270\217\340\270\264\340\270\232\340\270\261\340\270\225\340\270\264\340\270\201\340\270\262\340\270\243\340\271\200\340\270\231\340\270\267\340\271\211\340\270\255\340\271\200\340\270\242\340\270\267\340\271\210\340\270\255\340\270\236\340\270\267\340\270\212\340\270\224\340\271\211\340\270\247\340\270\242\340\270\233\340\270\261\340\270\215\340\270\215\340\270\262\340\270\233\340\270\243\340\270\260\340\270\224\340\270\264\340\270\251\340\270\220\340\271\214.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Crossec--\340\270\243\340\270\260\340\270\232\340\270\232\340\270\252\340\271\210\340\270\207\340\271\200\340\270\252\340\270\243\340\270\264\340\270\241\340\270\201\340\270\262\340\270\243\340\270\227\340\270\263\340\270\233\340\270\217\340\270\264\340\270\232\340\270\261\340\270\225\340\270\264\340\270\201\340\270\262\340\270\243\340\271\200\340\270\231\340\270\267\340\271\211\340\270\255\340\271\200\340\270\242\340\270\267\340\271\210\340\270\255\340\270\236\340\270\267\340\270\212\340\270\224\340\271\211\340\270\247\340\270\242\340\270\233\340\270\261\340\270\215\340\270\215\340\270\262\340\270\233\340\270\243\340\270\260\340\270\224\340\270\264\340\270\251\340\270\220\340\271\214.json"
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Debunker-ML-\340\270\225\340\270\243\340\270\247\340\270\210\340\270\210\340\270\261\340\270\232\340\270\202\340\271\210\340\270\262\340\270\247\340\270\245\340\270\247\340\270\207.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Debunker-ML-\340\270\225\340\270\243\340\270\247\340\270\210\340\270\210\340\270\261\340\270\232\340\270\202\340\271\210\340\270\262\340\270\247\340\270\245\340\270\247\340\270\207.json"
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Edge-to-Face-Drawing-Realistic-Faces-from-Canny-Edges.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Edge-to-Face-Drawing-Realistic-Faces-from-Canny-Edges.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Emotion-Detection-from-Facial-Micro-experessions.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Emotion-Detection-from-Facial-Micro-experessions.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Fake-Product-Detection-on-Online-Retail.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Fake-Product-Detection-on-Online-Retail.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Find-Water-from-Satellite-Images-Using-U-Net-Image-Segmentation-with-Pytorch.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Find-Water-from-Satellite-Images-Using-U-Net-Image-Segmentation-with-Pytorch.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Food-Ingredients-Label-Reader-for-Food-Allergy.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Food-Ingredients-Label-Reader-for-Food-Allergy.json
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/GANime-FullBody-\340\270\247\340\270\262\340\270\224\340\270\243\340\270\271\340\270\233\340\270\225\340\270\261\340\270\247\340\270\245\340\270\260\340\270\204\340\270\243\340\270\255\340\270\231\340\270\264\340\271\200\340\270\241\340\270\260(\340\270\252\340\270\262\340\270\247\340\271\206)\340\271\201\340\270\232\340\270\232\340\271\200\340\270\225\340\271\207\340\270\241\340\270\225\340\270\261\340\270\247-\340\270\224\340\271\211\340\270\247\340\270\242-Deep-Learning.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/GANime-FullBody-\340\270\247\340\270\262\340\270\224\340\270\243\340\270\271\340\270\233\340\270\225\340\270\261\340\270\247\340\270\245\340\270\260\340\270\204\340\270\243\340\270\255\340\270\231\340\270\264\340\271\200\340\270\241\340\270\260(\340\270\252\340\270\262\340\270\247\340\271\206)\340\271\201\340\270\232\340\270\232\340\271\200\340\270\225\340\271\207\340\270\241\340\270\225\340\270\261\340\270\247-\340\270\224\340\271\211\340\270\247\340\270\242-Deep-Learning.json"
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/My-Little-HR-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\233\340\270\243\340\270\260\340\271\200\340\270\241\340\270\264\340\270\231\340\271\200\340\270\207\340\270\264\340\270\231\340\271\200\340\270\224\340\270\267\340\270\255\340\270\231\340\270\255\340\270\262\340\270\212\340\270\265\340\270\236\340\270\252\340\270\262\340\270\242-IT-\340\271\203\340\270\231\340\270\233\340\270\243\340\270\260\340\271\200\340\270\227\340\270\250\340\271\204\340\270\227\340\270\242.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/My-Little-HR-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\233\340\270\243\340\270\260\340\271\200\340\270\241\340\270\264\340\270\231\340\271\200\340\270\207\340\270\264\340\270\231\340\271\200\340\270\224\340\270\267\340\270\255\340\270\231\340\270\255\340\270\262\340\270\212\340\270\265\340\270\236\340\270\252\340\270\262\340\270\242-IT-\340\271\203\340\270\231\340\270\233\340\270\243\340\270\260\340\271\200\340\270\227\340\270\250\340\271\204\340\270\227\340\270\242.json"
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Object-Detection-in-White-Blood-Cells-for-Leukemia.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Object-Detection-in-White-Blood-Cells-for-Leukemia.json
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Obstacle-Detection-for-Blind-people-\340\270\212\340\271\210\340\270\247\340\270\242\340\271\200\340\270\253\340\270\245\340\270\267\340\270\255\340\270\234\340\270\271\340\271\211\340\270\236\340\270\264\340\270\201\340\270\262\340\270\243\340\270\227\340\270\262\340\270\207\340\270\252\340\270\262\340\270\242\340\270\225\340\270\262\340\270\224\340\271\211\340\270\247\340\270\242-Deep-Learning.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Obstacle-Detection-for-Blind-people-\340\270\212\340\271\210\340\270\247\340\270\242\340\271\200\340\270\253\340\270\245\340\270\267\340\270\255\340\270\234\340\270\271\340\271\211\340\270\236\340\270\264\340\270\201\340\270\262\340\270\243\340\270\227\340\270\262\340\270\207\340\270\252\340\270\262\340\270\242\340\270\225\340\270\262\340\270\224\340\271\211\340\270\247\340\270\242-Deep-Learning.json"
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Plant-Disease-Classification.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Plant-Disease-Classification.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/RL-in-Traffic-Management.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/RL-in-Traffic-Management.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/TLDR;-Terms-and-Conditions-Summarizer.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/TLDR;-Terms-and-Conditions-Summarizer.json
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/TextDoe-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\210\340\270\263\340\271\201\340\270\231\340\270\201\340\271\201\340\270\247\340\270\224\340\270\247\340\270\207\340\270\232\340\270\227\340\270\204\340\270\247\340\270\262\340\270\241\340\270\252\340\270\264\340\271\210\340\270\207\340\270\236\340\270\264\340\270\241\340\270\236\340\271\214.json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/TextDoe-\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245\340\270\210\340\270\263\340\271\201\340\270\231\340\270\201\340\271\201\340\270\247\340\270\224\340\270\247\340\270\207\340\270\232\340\270\227\340\270\204\340\270\247\340\270\262\340\270\241\340\270\252\340\270\264\340\271\210\340\270\207\340\270\236\340\270\264\340\270\241\340\270\236\340\271\214.json"
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/Using-Machine-Learning-to-create-Auto-Pitch-Writer-for-UTAU.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/Using-Machine-Learning-to-create-Auto-Pitch-Writer-for-UTAU.json
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diff --git "a/_next/data/P1wceHoGgr6TnuCfa06o0/2022/\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245-CNN-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\270\201\340\270\262\340\270\243\340\270\210\340\270\263\340\271\201\340\270\231\340\270\201\340\270\252\340\270\261\340\270\215\340\270\215\340\270\262\340\270\223\340\270\252\340\270\241\340\270\255\340\270\207\340\271\203\340\270\231\340\270\243\340\270\260\340\270\232\340\270\232-SSVEP-BCI-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\271\204\340\270\241\340\271\200\340\270\201\340\270\243\340\270\231-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine).json" "b/_next/data/8Svqkuv7Is15opn2UcCBZ/2022/\340\271\202\340\270\241\340\271\200\340\270\224\340\270\245-CNN-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\270\201\340\270\262\340\270\243\340\270\210\340\270\263\340\271\201\340\270\231\340\270\201\340\270\252\340\270\261\340\270\215\340\270\215\340\270\262\340\270\223\340\270\252\340\270\241\340\270\255\340\270\207\340\271\203\340\270\231\340\270\243\340\270\260\340\270\232\340\270\232-SSVEP-BCI-\340\270\252\340\270\263\340\270\253\340\270\243\340\270\261\340\270\232\340\271\204\340\270\241\340\271\200\340\270\201\340\270\243\340\270\231-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine).json"
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diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/10-chonlana-kruawuthikun.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/10-chonlana-kruawuthikun.json
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diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/11-tharadon-jitsue.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/11-tharadon-jitsue.json
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+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/12-peemmaphat-sripongsai.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/13-pawan-jakkaew.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/13-pawan-jakkaew.json
new file mode 100644
index 0000000..ea8d310
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/13-pawan-jakkaew.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"13-pawan-jakkaew","content":"\n![image](/images/2024/13/01.png)\n\n-เป็นการใช้ Machine Learning เพื่อสร้าง Ai ในการแยกความผิดปรกติของโรคทางสายตาจากภาพถ่ายจอประสาทตา หรือเรียกว่า Ocular Disease Intelligent Recognition (ODIR)\n-โดย dataset ที่นำมาใช้ในครั้งนี้มาจาก kaggle โดยเป็นข้อมูลของโรงพยาบาลหลายๆแห่งในประเทศจีน โดยมีข้อมูลโดยรวมอยู่ประมาณ 6,000 ตัวอย่าง\n-ในครั้งนี้ ได้เลือกใช้ model vit ในการนำมาเทรน ซึ่งผลลัพธ์โดยรวมคือสามารถแยกโรคต่างๆได้ตรง ซึ่งอยู่ที่ประมาณ 0.88\n-ในส่วนของการแยกทดสอบรูปภาพแต่ละคลาสนั้นโมเดลสามารถตรวจจับความแม่นยำได้ถึง 98%\n-ในส่วนของความผิดพลาด ตัวโมเดลนี้อาจจะยังไม่สามารถแยกภาพถ่ายที่ถูกย้อมสีมาได้ หรือแยกได้ยาก ซึ่งน่าจะเป็นผลมาจาก ข้อมูลที่มีไม่มากพอและความชัดของข้อมูลร่วมด้วย\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ดิฉันคิดว่าโครงงานนี้จะช่วยพัฒนาทักษะต่างๆก็ดิฉันได้ดีมากยิ่งขึ้น อีกทั้งโครงงานนี้ยังเป็นโครงการที่มีเป้าหมายของโครงการตรงกับความสนใจของดิฉันอีกด้วย ดิฉันคิดว่าโครงงานนอกจากจะชวนพัฒนาตัวดิฉันเองแล้วนั้น โครงการนี้ก็เป็ฯโครงการที่ได้รับการยอมรับจากหลายๆมหาลัยอีกด้วย ดิฉันจึงมีความคิดที่จะทุ่มเทความสามารถ เพื่อที่จะทำทุกๆโครงงานที่เกิดขึ้นในโครงการนี้อย่างดีที่สุด\n    ","date":"31-7-24","title":"Ocular Disease Intelligent Recognition (ODIR)13","builder":"ปวรรณ จักรแก้ว(แตงโม)","builder_info":"สตรีวิทยา / กรุงเทพมหานคร","thumbnail":"/images/2024/13/01.png","links":{"github":"https://github.com/ppawanktm/Ai-builder-2024","facebook":"","blog":"https://medium.com/@pawanjakkaew24/ocular-disease-intelligent-recognition-odir-f52837a54464"}}},"__N_SSG":true}
\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/14-ratchakrit-mojomsin.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/14-ratchakrit-mojomsin.json
new file mode 100644
index 0000000..206a0e7
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/14-ratchakrit-mojomsin.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"14-ratchakrit-mojomsin","content":"\n![image](/images/2024/14/01.png)\n\n- ด้วยปัญหาความสะเพร่าในการตรวจจับสิ่งผิดปกติจากภาพกล้องวงจรปิดในปัจจุบัน การแก้ปัญหาด้วยการทำ Machine Learning model เพื่อให้การจำแนกเหตุการณ์ผิดปกติต่าง ๆ นั้นทำได้ง่ายและแม่นยำยิ่งขึ้น\n- รวบรวมข้อมูลจากชุดข้อมูล “Real Time Anomaly Detection in CCTV Surveillance” บนเว็บไซต์ kaggle โดยจะคัดเลือกจากเหตุการณ์ที่พบเจอได้บ่อยครั้ง\n- Clean Data ด้วยการสุ่มตัวอย่าง frame จากแต่ละช่วงของวิดีโอในจำนวนที่เท่ากันและนำมาประกอบกันหรือ Data Sampling เพื่อให้แต่ละไฟล์วิดีโอมีขนาดที่เท่ากัน แต่ยังคงสาระสำคัญที่เราต้องการไว้\n- เลือกใช้ Pre-trained model อย่าง ViViT มา fine-tune กับชุดข้อมูลที่เก็บรวบรวมมาโดยได้ผล Accuracy อยู่ที่ 95% และ F1 Score ประมาณ 0.94\n- ใช้ Streamlit ในการทำ Web application และ Deploy โมเดลที่สามารถ Classification วิดีโอจากกล้องวงจรปิดได้\n- จากแบบทดสอบการจำแนกเหตุการณ์จากภาพกล้องวงจรปิด เมื่อนำรูปภาพในแบบทดสอบให้ตัวโมเดล Machine Learning ที่มีความแม่นยำ 95% ทำนายผลแล้ว ปรากฎว่าตัวโมเดลนั้นทำนายเหตุการณ์ได้ถูกหมดในทุก ๆ ข้อ\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ผมเป็นนักเรียนโครงการห้องเรียน พสวท. (สู่ความเป็นเลิศ) ศูนย์โรงเรียนยุพราชวิทยาลัย จังหวัดเชียงใหม่ ผมมีความสนใจทำโครงงานที่มีการประยุกต์ใช้ความรู้ทางคณิตศาสตร์และความรู้ทางเทคโนโลยีในการแก้ปัญหาในชีวิตประจำวัน หรือปัญหาในชุมชน ที่สามารถนำไปใช้แก้ปัญหาได้จริง จากข่าวสารและการสำรวจพื้นที่จริง<br>จากเหตุผลดังกล่าวทำให้ผมมีความสนใจในการเข้าร่วมโครงการ ai builders เพื่อสร้างผลงานโดยใช้เทคนิคทางด้านวิทยาศาสตร์ข้อมูล (data science) และปัญญาประดิษฐ์ (artificial intelligence)\n    ","date":"31-7-24","title":"CCTV Anomaly Detection","builder":"รัชกฤช โมจมสิน(โอ๊ค)","builder_info":"ยุพราชวิทยาลัย / เชียงใหม่","thumbnail":"/images/2024/14/01.png","links":{"github":"https://github.com/ratchy-oak/CCTV_Anomaly_Detection","facebook":"","blog":"https://medium.com/@ratchy-oak/%EF%B8%8F-%EF%B8%8F-cctv-anomaly-detection-1545f7bbbe93"}}},"__N_SSG":true}
\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/2-ananya-kanaraksanti.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/2-ananya-kanaraksanti.json
new file mode 100644
index 0000000..13d9877
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/2-ananya-kanaraksanti.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"2-ananya-kanaraksanti","content":"\n![image](/images/2024/2/01.png)\n\n- จำแนกประเภทแผลที่พบได้ในการใช้ความรุนแรงในครอบครัวตามประภทอาวุธที่ใช้และลักษณะการเกิดแผลเพื่อการคัดกรองเหยื่อที่เร็วและแม่นยำมากขึ้นแม้จะไม่ได้เป็นผู้เชี่ยวชาญ\n- เก็บชุดข้อมูลจาก Kaggle และ DuckDuckGo Image Search API ซึ่งภาพมี noise เยอะและคุณภาพไม่ดี หลังจากทำความสะอาดทำให้ได้ imbalanced dataset แบ่ง Training-validation-test split ที่ 80:10:10 และใช้ baseline model จากโมเดลบน kaggle\n- upsampling ข้อมูลก่อนนำเข้า augmentation เทรนด้วยสถาปัตยกรรม Resnet34 และใช้ weighted cross entropy loss ด้วย effective number of samples (ENS) มี accuracy อยู่ที่ 86% และ F1-score ที่ 83%\n- โมเดลค่อนข้าง sensitive กับการ crop และสัดส่วนของภาพ จึงเพิ่มการ crop ในขั้นตอน upsampling และ augmentation เทรนด้วยสถาปัตยกรรม Resnet50 ซึ่งสามารถ sensitivityจากการ crop ในบางภาพได้แต่การ crop ก็ยังคงส่งผลต่อการทำนายของโมเดลในบางภาพ\n- เมื่อทดสอบโมเดลบน testing set มี accuracy อยู่ที่ 82% และ F1-score ที่ 79% ซึ่งสูงกว่า baseline model แต่ยังคงต้องการ dataset ที่ใหญ่ขึ้นในการพัฒนาโมเดลและในอนาคตต้องการพัฒนาโมเดลให้สามารถระบุอาวุธที่ใช้จากภาพได้\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ตอนแรกได้รู้จัก ai builders ในปี 2022 เด็กคนนั้นที่เขียน python ได้บ้าง เข้ามาด้วยเหตุผลคล้าย ๆ กับคนอื่น ทั้งอยากจะเขียนโปรแกรมให้เก่งขึ้น อยากลองทำai เลยลองสมัครดู แต่ก็ติดอยู่คำถามที่ว่า “โครงงานที่อยากทำคืออะไร” ที่หาคำตอบไม่ได้ คำถามนี้ทำให้เรากลับมาคิดว่าเราจะเอาความสามารถที่เรามีไป ‘สร้าง’ อะไรกันแน่การไม่ผ่านการคัดเลือกในครั้งนั้นทำให้เรามองโลกต่างจากเดิม เห็นpain pointหลาย ๆ จุดที่เราไม่คิดว่ามันจะเป็นปัญหา ทำให้เราอยากเอาตัวเองเข้าไปแก้ปัญหาจุดนั้นจุดนี้ อยากจะเอาskillที่มีไปใส่ในแต่ละงานแน่นอนว่าการเก็บเกี่ยวและพัฒนาskillด้านaiของตัวเองเป็นเป้าหมายหนึ่งในการเข้าร่วมโครงการในปีนี้ การรับผิดชอบโปรเจกนึง การเรียนรู้ด้วยตัวเอง การเรียนรู้จากคนรอบข้าง ทั้งหมดเป็นเรื่องที่challengeสำหรับเรามาก ๆ และเราเชื่อว่ามันจะเป็นskillพื้นฐานที่ดีก่อนจะเข้าเป็นนักศึกษาวิศวกรรมศาสตร์คอมพิวเตอร์เต็มตัวในอีกไม่กี่เดือนข้างหน้าอีกความคาดหวังที่เชื่อว่าโครงการนี้จะตอบโจทย์เราได้ไม่แพ้กันและตัวเราเองก็ตอบโจทย์คืออยากเป็นอีกหนึ่งมุมมองที่จะหยิบยกหลาย ๆ ปัญหาที่ไม่ได้ถูกnoticeเท่าที่ควร แลกเปลี่ยนความเห็นกับทั้งเพื่อนค่ายและเมนเทอร์ เกิดเป็นshowcaseใหม่ ๆ ที่หลากหลายมากขึ้นและได้เป็นส่วนหนึ่งของ communityไม่ช้าก็เร็วเราเชื่อว่าตรงนี้จะเป็นจุดเริ่มต้นเล็ก ๆ\n    ","date":"31-7-24","title":"Wound classification model","builder":"อนัญญา คณารักษ์สันติ(ไจไหม)","builder_info":"ดรุณสิกขาลัย (โครงการวมว.) / กรุงเทพมหานคร","thumbnail":"/images/2024/2/01.png","links":{"github":"https://github.com/ananyaknr/wound-classification","facebook":"","blog":"https://medium.com/@jaimai2006/wound-classification-3d89dee6d402"}}},"__N_SSG":true}
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diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/3-nattavee-sunitsakul.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/3-nattavee-sunitsakul.json
new file mode 100644
index 0000000..4a9dd9a
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/3-nattavee-sunitsakul.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"3-nattavee-sunitsakul","content":"\n![image](/images/2024/3/01.png)\n\n- โมเดลแนะนำว่าควรปลูกพืชอะไร โดยเน้นพืชเศรษฐกิจของไทย\n- สร้าง dataset จาก public data ของได้ ได้แก่ ข้อมูล soil series data จาก กรมพัฒนาที่ดิน ข้อมูลรายละเอียดของดิน จาก สำนักสำรวจดินและวิจัยทรัพยากรดิน และข้อมูลจากระบบการติดตามสถานการณ์เพาะปลูกพืชเศรษฐกิจในประเทศไทยจากข้อมูลดาวเทียม จาก GISTDA และนำมาสร้าง tabular data ด้วยการทำ grid และแบ่ง train valid test โดยใช้ spatial train valid test split\n- วัดผลโดยใช้ top-k accuracy matric\n- XGBoost, Catboost, และ KNN ทำออกมาได้ดีพอ ๆ กัน โดยได้ top-k accuracy score (k=1) อยู่ที่ 80.6%, 83.2%, และ 89.4%\n- เมื่อเทียบกับ Most Frequent Classตามผลเฉลยที่เป็นไปได้มากที่สุด top-k accuracy score (k=1) อยู่ที่ 58.7%\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ผมเห็นเพื่อนปีที่แล้วได้เข้าโครงการ ai builder แล้วบอกต่อมาว่าโครงการนี้ดีมาก ๆ สำหรับมาฝึกทำ ai ได้ทำ project ai จริง ๆ แล้วมีอาจารย์ที่ปรึกษาตัวตึงอีกหลาย ๆ ท่านค่อยให้คำปรึกษา ประกอบกับผมเองสนใจและอยากเรียนรู้เกี่ยวกับ ai มากยิ่งขึ้น ซึ่งผมคิดว่าค่าย ai builder จะช่วยสานฝันให้โปรเจค ai ที่ผมอยากทำทำได้จริง ๆ ครับ อีกทั้งช่วงที่ทางโครงการจัดยังเป็นช่วงปิดเทอมซึ่งเป็นช่วงเวลาที่ว่าง และอยากลงทุนกับการศึกษาเกี่ยวกับ ai เพิ่มเติมครับ\n    ","date":"31-7-24","title":"Crop Recommendation System for Thai Economic Plants","builder":"ณัฐวีณ์ สุนิตย์สกุล( ตัง)","builder_info":"ดรุณสิกขาลัย (โครงการ kosen kmutt) / กรุงเทพมหานคร","thumbnail":"/images/2024/3/01.png","links":{"github":"https://medium.com/@tangnatta/%E0%B9%80%E0%B8%A3%E0%B8%B2%E0%B8%84%E0%B8%A7%E0%B8%A3%E0%B8%9B%E0%B8%A5%E0%B8%B9%E0%B8%81%E0%B8%AD%E0%B8%B0%E0%B9%84%E0%B8%A3%E0%B8%94%E0%B8%B5-w-summary-fa9d7661e138","facebook":"","blog":"https://medium.com/@tangnatta/%E0%B9%80%E0%B8%A3%E0%B8%B2%E0%B8%84%E0%B8%A7%E0%B8%A3%E0%B8%9B%E0%B8%A5%E0%B8%B9%E0%B8%81%E0%B8%AD%E0%B8%B0%E0%B9%84%E0%B8%A3%E0%B8%94%E0%B8%B5-w-summary-fa9d7661e138"}}},"__N_SSG":true}
\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/4-sittipark-kaewka.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/4-sittipark-kaewka.json
new file mode 100644
index 0000000..a2af167
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/4-sittipark-kaewka.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"4-sittipark-kaewka","content":"\n![image](/images/2024/4/01.png)\n\n- โมเดลจำแนกรูปภาพแมงมุม 15 สายพันธุ์ที่พบเจอได้ในหลาย ๆ พื้นที่ทั้งในประเทศไทยและต่างประเทศ\n- วัดผลเทียบกับบุคคลทั่วไป รวมถึงผู้ที่พอมีความรู้ด้านแมงมุมจำนวน 20 คน ด้วย mini-validation set 15 รูป มีค่าเฉลี่ยที่ 46.33% และทำได้ดีที่สุด 73.33%\n- รวมรวมชุดข้อมูลจาก Kaggle รวมถึงหารูปภาพเองเพิ่มเติมจากแหล่งต่าง ๆ เช่น Facebook, YouTube แล้วมาคัดเลือกรูปภาพด้วยตนเอง โดยแบ่งออกเป็น train 85% และ test 15%\n- ทดสอบกับสถาปัตยกรรม GoogLeNet, ResNet34 และ VGG-19 พบว่า VGG-19 ได้ผลดีที่สุดที่ accuracy 91% บน test set\n- เทียบกับมนุษย์บน mini-validation set โมเดลทำได้ 92% เทียบกับมนุษย์ที่เก่งที่สุดที่ 73.33%\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ที่ผมอยากเข้าโครงการ <strong>al builders</strong> เพราะว่าผมอยากพัฒนาศักยภาพของตัวเองด้าน ai ครับ เผื่อมีบางเนื้อหาที่ผมยังไม่เข้าใจหรือบางส่วนที่ผมขาดตกบกพร่องไป ผมจะได้ใช้โอกาสที่ได้เข้าไปในโครงการ ai builders และตั้งใจเรียนรู้กับมัน นอกจากนี้ผมก็อยากฝึกทักษะการแก้ปัญหาด้วยครับ ผมรู้สึกว่ามันเป็นทักษะที่สำคัญในโลกยุคปัจจุบันมาก ๆ โดยผมรู้สึกสนใจในศาสตร์ด้านนี้มาตั้งแต่ช่วง ม.4 ครับ ผมเลยอยากเข้าโครงการนี้มาก ๆ ครับ ผมอยากจะพิสูจน์ตัวเองว่าผมก็สามารถพัฒนาตนเองให้เก่งขึ้นในด้าน ai ได้เหมือนกันคร้บ\n    ","date":"31-7-24","title":"Spider Classification","builder":"สิทธิภาคย์ แก้วกา(ไออุ่น)","builder_info":"ราชวินิตบางแก้ว / สมุทรปราการ","thumbnail":"/images/2024/4/01.png","links":{"github":"https://github.com/Sittipark/Spider_Classification_AIB","facebook":"","blog":"https://medium.com/@kaewka1971/spider-classification-%E0%B9%81%E0%B8%A1%E0%B8%87%E0%B8%A1%E0%B8%B8%E0%B8%A1-15-%E0%B8%AA%E0%B8%B2%E0%B8%A2%E0%B8%9E%E0%B8%B1%E0%B8%99%E0%B8%98%E0%B8%B8%E0%B9%8C-%EF%B8%8F-2f67dc5c0b7b"}}},"__N_SSG":true}
\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/5-nontapat-auetrongjit.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/5-nontapat-auetrongjit.json
new file mode 100644
index 0000000..ec3e6f6
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/5-nontapat-auetrongjit.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"5-nontapat-auetrongjit","content":"\n![image](/images/2024/5/01.png)\n\n- สร้างโมเดล Student Behavior Detector ช่วยแก้ปัญหาและเพิ่มประสิทธิภาพการเรียนรู้ของนักเรียน\n- การสร้าง Student Behavior Detector เป็นการใช้สถาปัตยกรรม YOLO  หลักการคือ มันจะพยายาม rectangle object เหล่านั้นไว้ (โดยหาจุดกึ่งกลางของแต่ละ object แล้วค่อยครอบ box เอาไว้) และบอกออกมาว่าสิ่งนั้นคืออะไร โดยมี model พื้นฐานอยู่แล้วประมาณ 80 classes ที่ถูกเทรนเอาไว้ และสามารถบอกได้ด้วยว่าความน่าจะเป็นมีเท่าไหร่ จาก model ที่มี\n- ใช้ Dataset จาก SCB-dataset3-S แล้วนำมา split data อีกทีด้วยวิธี K-Fold Cross-Validation ได้ 5 Dataset ที่แตกต่างกัน\n- ในส่วนของการเทรนได้ทดลองใช้สถาปัตยกรรม YOLOv8x , YOLOv9e และ YOLOv10x\n-วัดผลโดยการประเมิน Precision ,Recall ,mAP50 ,mAP50-95\nโดยได้ผลออกมาคือ YOLOv9e ทำ performance ออกได้ดีที่สุดบน Test set คือ \n(fold0) Precision : 70.1 % ,Recall : 74.6% , mAP50 : 77.6 % , mAP50-95 : 60.5 %\n(fold2) Precision : 75.2% ,Recall : 70.5% , mAP50 : 77.4 % , mAP50-95 : 61.1 %\n(fold3) Precision : 72.2 % ,Recall : 73% , mAP50 : 77.8 % , mAP50-95 : 61.1 %\n ซึ่ง fold0 จะมีค่า Recall สูงสุด และ fold2 จะมีค่า Precision สูงสุด และ fold3 จะสมดุลระหว่าง Precision กับ Recall\n-เทียบกับ SCB-dataset3 ที่ train YOLOv7x ไว้ ค่า Precision Recall mAP50 และ mAP50-95 ของเราจะต่ำกว่าเล็กน้อยเนื่องจากเรา split data ทำให้จำนวน train data น้อยลง แต่จะทำให้สามารถมั่นใจได้ว่า โมเดลของเราจะทำงานมีประสิทธิภาพประมาณนี้กับข้อมูลที่ไม่เคยเห็นมาก่อน \n-จาการวิเคราะห์ข้อผิดพลาดของตัว Student Behavior Detector พบว่าโมเดลมักทำนายไม่แม่นย่ำเมื่อเจอ class writting ซึ่งคาดว่าน่าจะมาจากจำนวน data class writting นั้นมีน้อยกว่า class อื่นๆ และพบว่า model ชอบทายวงที่ background อยู่ คาดว่าจำนวน data นั้นน้อยเกินไป\n\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ผมสนใจค่ายนี้เป็นอย่างมากครับ เมื่อปีที่แล้วผมก็สมัครเข้าโครงการแต่ไม่ได้รับคัดเลือกเข้าโครงการ เนื่องจากมีเวลาเตรียมตัวน้อยติดช่วงสอบปลายภาคยังบริหารเวลาได้ไม่ดี แต่ครั้งนี้ผมตั้งใจเต็มที่ที่จะมาเข้าค่ายให้ได้ เนื่องจากผมอยากมีความรู้เพิ่มเติมในการทำ senior project ก่อนจบมัธยมศึกษาตอนปลาย ผมอยากได้ทั้งความรู้ คำแนะนำและอาจารย์ที่ปรึกษามาช่วยแนะนำโครงการที่เกี่ยวกับ ai facial recognition ไม่เพียงแต่สร้างโปรแกรมได้ แต่ต้องการต่อยอดไปเป็นระบบการเช็คชื่อเข้าเรียนในโรงเรียนของผมด้วยครับ ซึ่งที่ รร. ของผมยังไม่มีผู้เชี่ยวชาญที่จะให้คำแนะนำในเรื่องนี้และช่วงปิดเทอมนี้ผมต้องทำ senior project เกี่ยวกับ ai ที่ผมสนใจให้สำเร็จภายในเดือน ส.ค นี้ ผมหวังเป็นอย่างยิ่งว่าทางสถาบันฯจะให้โอกาสผมได้เข้าไปเรียนรู้กับอาจารย์ผู้ทรงคุณวุฒิ และได้รับคำปรึกษาจากการเข้าค่ายครั้งนี้ครับ และผมสัญญาว่าจะเอาความรู้ความสามารถไปแบ่งปันประสบการณ์ให้กับเพื่อนๆ น้องๆ ที่ รร. เพื่อต่อยอดในการประดิษฐ์ ai ใหม่ๆ ในอนาคตครับ นอกจากนี้ผมเองก็สนใจด้าน ai เป็นอย่างมาก และตั้งเป้าหมายที่จะเรียนและทำงานด้านนี้ เพื่อทำให้คนไทยได้มีโอกาสพัฒนา นวัตกรรมใหม่ๆให้กับคนไทย ผมภูมิใจที่ได้ทราบว่าประเทศไทยมี thailand digital valley ซึ่งจะเป็นแหล่งรวมของคน it และ start up รุ่นใหม่ ทั้งในประเทศและต่างประเทศ อยู่ที่นี่และ\n    ","date":"31-7-24","title":"Student Behavior Detector in Classroom","builder":"นนทพัทธ์ เอื้อตรงจิตต์(เฟิร์ม)","builder_info":"สาธิตแห่งมหาวิทยาลัยเกษตรศาสตร์ ศูนย์วิจัยและพัฒนาการศึกษา / กรุงเทพมหานคร","thumbnail":"/images/2024/5/01.png","links":{"github":"https://github.com/nontaphatfirm/Classroom-Behavior-Detector","facebook":"","blog":"https://medium.com/@nontaphatfirm/student-behavior-detector-in-classroom-20f2fe5cc8a3"}}},"__N_SSG":true}
\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/6-thanaphum-saywongin.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/6-thanaphum-saywongin.json
new file mode 100644
index 0000000..a899b55
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/6-thanaphum-saywongin.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"6-thanaphum-saywongin","content":"\n![image](/images/2024/6/01.png)\n\n- สร้างโมเดล AniRec มาเพื่อแก้ปัญหาการตามหาชื่อเรื่องอนิเมะโดยใช้ภาพจากซีนในอนิเมะ\n- การสร้าง AniRec นั้นจะแบ่งเป็นส่วนของการเทรน classification model และนำไปทำ feature extraction โดย match retrieved image กับ label และนำทั้ง classification และ retrieval มาเปรียบเทียบกัน\n- ใช้ Dataset เป็น Top 100 Popularity Anime จาก Anilist โดยเลือกเฉพาะรูปที่เป็นซีนใน episode ต่าง ๆ\n- นำข้อมูลทั้งหมดมาเข้ากระบวนการ Preprocessing ด้วยการทำ Data Tranformation ทั้งการ Resize, ToTensor, Normalize และ Data Augmentation รูปแบบต่าง ๆ\n- ในส่วนของการเทรนได้ทดลองใช้สถาปัตยกรรม MobileNetV2 , Efficientnet-B0 , EFficientnet-B7 , ResNeXt101 และ SEResNeXt101\n- วัดผลโดยการประเมิน Accuracy, Top-5 Accuracy , LRAP และ MRR\n- โดยได้ผลออกมาคือ ResNeXt101 ทำ performance ออกได้ดีที่สุดบน Test set คือ Accuracy 81.18% Top-5 Accuracy 92.48% LRAP 86.24% และ MRR 85.75%\n- จากนั้นจึงนำ ResNeXt101 มาทำ feature extraction โดยได้ match retrieved image กับ label ไว้ก่อนเพื่อนำมาใช้ในทำนาย label\n- นำมา retrieve โดยใช้ similarity measurement เป็น Euclidean distance\n- ทำการทดสอบการทำนายของ retrieval โดยได้ผลลัพธ์ดังนี้\n- Accuracy 81.18% Top-5 Accuracy 91.84% LRAP 81.24% และ MRR 82.35%\n- AniRec จึงเลือกใช้ Classification ResNeXt101 ซึ่งมี performance ที่ดีที่สุด\n- โดยเมื่อนำไปเทียบกับ trace.moe ซึ่งเป็น Anime reverse search ที่มีชื่อเสียง โดยได้ทดสอบบน Test set เดียวกันได้ผลลัพธ์ดังนี้ Accuracy 67.40% และ Top-5 Accuracy 70.13%\n- ซึ่งตัว AniRec ทำ Accuracy ได้ดีกว่า trace.moe ถึง 13.78% และ Top-5 Accuracy ดีกว่าถึง 22.35% แตว่าก็ยังแพ้ในจำนวนเรื่องของอนิเมะที่ค้นหาได้\n- จาการวิเคราะห์ข้อผิดพลาดของตัว AniRec พบว่าโมเดลมักทำนายผิดพลาดเมื่อเจอซีนที่มีความคล้ายกัน ทั้งจากตัวประกอบที่อาจไม่มีข้อมูลใน Training Data และ องค์ประกอบของซีนที่บังเอิญคล้ายกันในอนิเมะหลาย ๆ เรื่อง\n\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> เพราะว่าตัวผมอยากที่จะพัฒนาความรู้ทางด้าน ai ให้มากขึ้น แม้ว่าในตอนนี้เองก็กำลังศึกษาด้วยตัวเองอยู่ แต่การได้เข้าร่วมโครงการ ai builder ซึ่งเต็มไปด้วยวิทยากรที่มีความสามารถ อีกทั้งยังทำให้ตัวผมได้มีโอกาสได้พบเจอเพื่อนๆที่สนใจในด้านเดียวกัน ดังนั้นผมจึงเชื่อว่าการเข้าร่วมโครงการนี้นั้นจะทำให้ผมสามารถพัฒนาความรู้ด้าน ai และ ทักษะด้านการทำงานต่างๆ ได้เป็นอย่างดีครับ\n    ","date":"31-7-24","title":"AniRec","builder":"ธนภูมิ สายวงศ์อินทร์(อิคคิว)","builder_info":"วิทยาศาสตร์จุฬาภรณราชวิทยาลัย เชียงราย / เชียงราย","thumbnail":"/images/2024/6/01.png","links":{"github":"https://github.com/qrcodeTH/Anime-Recognition-System-from-Scene-Images/tree/main","facebook":"","blog":"https://medium.com/@thanaphum04571/anime-recognition-system-from-scene-images-anirec-%E0%B8%A3%E0%B8%B0%E0%B8%9A%E0%B8%B8%E0%B8%8A%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B9%80%E0%B8%A3%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B8%87%E0%B8%88%E0%B8%B2%E0%B8%81%E0%B8%A0%E0%B8%B2%E0%B8%9E%E0%B8%8B%E0%B8%B5%E0%B8%99%E0%B8%AD%E0%B8%99%E0%B8%B4%E0%B9%80%E0%B8%A1%E0%B8%B0-c0133dbbfaa9"}}},"__N_SSG":true}
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diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/7-guntee-doungmanee.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/7-guntee-doungmanee.json
new file mode 100644
index 0000000..7e6091a
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/7-guntee-doungmanee.json
@@ -0,0 +1 @@
+{"pageProps":{"postData":{"id":"7-guntee-doungmanee","content":"\n![image](/images/2024/7/01.png)\n\n- สร้างโมเดล ThaiVecFont สำหรับการสร้างฟอนต์เพื่อลดปัญหาการทำงานซ้ำๆ ของนักออกแบบฟอนต์ไทย และเป็นโมเดลสำหรับสร้างฟอนต์ SVG ที่สามารถนำไปใช้งานได้จริงได้\n- เป็นการใช้สถาปัตยกรรม DeepVecFont-V2 ที่มีพื้นฐานเป็น Transformers Autoencoder โดยมี Encoder และ Decoder อย่างละ 2 ตัว\n- ใช้ Dataset ที่ scrape จาก thaifaces.com เว็บคุณภาพที่รวบรวมฟอนต์ไทยจากทุกทิศทางเอาไว้ \nทำ Data Cleaning ฟอนต์ที่ขนาดใหญ่และเล็กเกินไปออก\n- Preprocessing ด้วยการแปลงไฟล์ฟอนต์ให้เป็นรูปภาพและ vector sequence ทำการคัดฟอนต์ที่มีจำนวน sequence มากเกินไปออก ทำ Data Augmentation และใช้เทคนิค relaxation representation เพื่อเพิ่มจำนวนจุดให้กับ sequence ทำให้ตอนเทรนได้ผลดีขึ้น\n- ใช้เทคนิค Modality Fusion รวม feature ระหว่าง Encoder 2 ตัวเข้าด้วยกัน เพื่อให้โมเดลสามารถเข้าใจรูปร่างและโครงสร้างของฟอนต์ไปพร้อมกันได้\n- ปรับค่า weight โดยใช้ Loss คำนวนจาก L1 Loss จากการสร้างรูปภาพและ Cross Entropy Loss จากการสร้าง vector sequence\n- เมื่อเปรียบเทียบกับโมเดล DeepVecFont เวอร์ชั่นแรกที่ใช้ CNN เป็น Encoder ผลที่เกิดขึ้นคือเวอร์ชั่นแรกไม่สามารถจับลักษณะของฟอนต์ภาษาไทยได้ แต่ DeepVecFont-V2 สามารถทำได้\n- วัดผลโดยการประเมิน L1 Error ของรูปภาพ พบว่าโมเดล DeepVecFont-V2 ที่เทรนด้วยชุดข้อมูลที่มีการทำ Augmentation ให้ผลที่ดีกว่าแบบที่เทรนด้วยชุดข้อมูลปกติ\n- ข้อเสนอแนะ (เพิ่มเติม) ประสิทธิภาพโมเดลที่ได้ยังไม่ดีเท่าโมเดล DeepVecFont-V2 ที่เทรนด้วยชุดข้อมูลภาษาอังกฤษที่มีขนาดใหญ่ คาดว่าเนื่องจากจำนวนชุดข้อมูลฟอนต์ภาษาไทยที่ไม่เพียงพอ จึงคิดหาวิธีแก้โดยอาจมีการทดลอง fine-tuning โมเดล pretrained ภาษาอังกฤษด้วยชุดข้อมูลภาษาไทยในอนาคต รวมถึงหาวิธีใหม่ ๆ ในการเพิ่มชุดข้อมูล\n\n### แรงจูงในในการเข้าร่วมโครงการ (จากใบสมัครเข้าร่วมเมื่อ 10 สัปดาห์ที่แล้ว)\n\n> ปีที่แล้วผมไม่ติดโครงการนี้ ปีนี้เลยอยากจะแก้มือใหม่ ผมเชื่อในการเรียนรู้แบบ based on project ว่ามันจะช่วยพัฒนาสกิลเราขึ้นได้อย่างก้าวกระโดด หากยิ่งมีคนที่คอย support เรามากผลที่ได้มันยิ่งมหาศาลมากขึ้นไปอีกมาก การเข้าโครงการนี้จะเปิดโอกาสให้ผมสามารถทำสิ่งที่ผมชอบได้ หลายๆ อย่างที่เป็นไปไม่ได้ ผมเชื่อว่า มันสามารถที่จะเป็นไปได้ ถ้าเราทุ่มเทให้สุดแรงลงไป รวมถึงมีคน support ที่ดี โครงการนี้จะทำให้ผมได้ connection กับเพื่อน ๆ พี่ ๆ นักวิจัยนักพัฒนา ai แนวหน้าของประเทศและจะได้ต่อยอดไปในการทำงานในอนาคตได้ ที่สำคัญ ผมจะได้เจอคนทำ wangchanberta ตัวเป็นๆ ยังไม่พอ สามารถปรึกษาได้ด้วยอีก !!\n    ","date":"31-7-24","title":"Synthesize High-Quality Thai Vector Fonts","builder":"กันต์ธีร์ ดวงมณี(พอเพียง)","builder_info":"ยุพราชวิทยาลัย / เชียงใหม่","thumbnail":"/images/2024/7/01.png","links":{"github":"https://github.com/microhum/ThaiVecFont","facebook":"","blog":"https://medium.com/@guntee12123/synthesize-high-quality-thai-vector-fonts-with-deepvecfont-v2-a123317e1910"}}},"__N_SSG":true}
\ No newline at end of file
diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/8-nattapat-emseedaeng.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/8-nattapat-emseedaeng.json
new file mode 100644
index 0000000..473453a
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/8-nattapat-emseedaeng.json
@@ -0,0 +1 @@
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diff --git a/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/9-benyapa-takhwankeaw.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/9-benyapa-takhwankeaw.json
new file mode 100644
index 0000000..5c43b02
--- /dev/null
+++ b/_next/data/8Svqkuv7Is15opn2UcCBZ/2024/9-benyapa-takhwankeaw.json
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diff --git a/_next/data/P1wceHoGgr6TnuCfa06o0/index.json b/_next/data/8Svqkuv7Is15opn2UcCBZ/index.json
similarity index 89%
rename from _next/data/P1wceHoGgr6TnuCfa06o0/index.json
rename to _next/data/8Svqkuv7Is15opn2UcCBZ/index.json
index 91f0996..2b34c87 100644
--- a/_next/data/P1wceHoGgr6TnuCfa06o0/index.json
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10qsrqw">.css-10qsrqw{transition-property:var(--chakra-transition-property-common);transition-duration:var(--chakra-transition-duration-fast);transition-timing-function:var(--chakra-transition-easing-ease-out);cursor:pointer;-webkit-text-decoration:none;text-decoration:none;outline:2px solid transparent;outline-offset:2px;color:inherit;}.css-10qsrqw:hover,.css-10qsrqw[data-hover]{-webkit-text-decoration:none;text-decoration:none;}.css-10qsrqw:focus,.css-10qsrqw[data-focus]{box-shadow:var(--chakra-shadows-outline);}</style><a class="chakra-link css-10qsrqw" href="/showcase/2024/1-paphada-saengpridikorn"><style data-emotion="css 9vp29i">.css-9vp29i{width:100%;height:200px;}</style><div class="css-9vp29i"><style data-emotion="css bh4wo8">.css-bh4wo8{object-fit:cover;width:100%;height:100%;}</style><img alt="Color Harmony Classifier ML (CoHaML)" src="/showcase/images/2024/1/01.png" class="chakra-image css-bh4wo8"/></div><style data-emotion="css 1fh9ko">.css-1fh9ko{color:var(--chakra-colors-gray-50);font-weight:var(--chakra-fontWeights-bold);font-size:90%;width:100%;height:62.5px;background-color:var(--chakra-colors-blackAlpha-300);-webkit-padding-start:var(--chakra-space-4);padding-inline-start:var(--chakra-space-4);-webkit-padding-end:var(--chakra-space-4);padding-inline-end:var(--chakra-space-4);padding-top:var(--chakra-space-2);padding-bottom:var(--chakra-space-2);}</style><div class="css-1fh9ko"><div class="css-0"><style data-emotion="css 8uhtka">.css-8uhtka{overflow:hidden;text-overflow:ellipsis;white-space:nowrap;}</style><p class="chakra-text css-8uhtka">Color Harmony Classifier ML (CoHaML)</p><p class="chakra-text css-8uhtka">ปภาดา แสงปรีดีกรณ์(หมูแดง)</p></div></div></a></div></div></div><div tabindex="0" aria-labelledby="tabs-1--tab-1" role="tabpanel" hidden="" id="tabs-1--tabpanel-1" class="chakra-tabs__tab-panel css-a5mhaz"><div class="css-bcb7hj"><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/101-digital-textile-printing-defect-classification"><div class="css-9vp29i"><img alt="Digital Textile Printing Defect Classification" src="/showcase/images/2023/101/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Digital Textile Printing Defect Classification</p><p class="chakra-text css-8uhtka">Settapun Laoaree</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/102-pimthaigans"><div class="css-9vp29i"><img alt="pimthaigans" src="/showcase/images/2023/102/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">pimthaigans</p><p class="chakra-text css-8uhtka">Supawit Marayat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/103-marching-waifu"><div class="css-9vp29i"><img alt="marching-waifu-x: Diffusion models are zero-shot 3D character generators, too" src="/showcase/images/2023/103/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">marching-waifu-x: Diffusion models are zero-shot 3D character generators, too</p><p class="chakra-text css-8uhtka">Tawin Jiramahapokee</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/104-lo-fi-music"><div class="css-9vp29i"><img alt="Lo-Fi music style transfer" src="/showcase/images/2023/104/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Lo-Fi music style transfer</p><p class="chakra-text css-8uhtka">Thanakit Chongwilaikasem/มัธยมศึกษาปีที่ 4.0</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/105-pytorch-thai-food-image-classification"><div class="css-9vp29i"><img alt="Pytorch Thai food image classification" src="/showcase/images/2023/105/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Pytorch Thai food image classification</p><p class="chakra-text css-8uhtka">Saktanuth Praditukrit</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/106-plank-form-checker"><div class="css-9vp29i"><img alt="Plank Form Checker" src="/showcase/images/2023/106/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Plank Form Checker</p><p class="chakra-text css-8uhtka">Thee Kittivorapat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/107-dog-emotions"><div class="css-9vp29i"><img alt="Dog emotions" src="/showcase/images/2023/107/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Dog emotions</p><p class="chakra-text css-8uhtka">Thirada Thomnam</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/109-profanityguard-youtube"><div class="css-9vp29i"><img alt="ProfanityGuard ตรวจจับคำหยาบด้วย AI ก่อนนำไปลง Youtube" src="/showcase/images/2023/109/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">ProfanityGuard ตรวจจับคำหยาบด้วย AI ก่อนนำไปลง Youtube</p><p class="chakra-text css-8uhtka">Pasit Khumsena</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/110-th-en-MT"><div class="css-9vp29i"><img alt="TH-EN Machine Translation" src="/showcase/images/2023/110/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TH-EN Machine Translation</p><p class="chakra-text css-8uhtka">Tarit Witworrasakul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/111-object-detection-for-cctv-with-traffic"><div class="css-9vp29i"><img alt="Object detection for CCTV with traffic" src="/showcase/images/2023/111/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Object detection for CCTV with traffic</p><p class="chakra-text css-8uhtka">Kontuch Suksawat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/112-search-engine-with-automatic-tag-recommendation"><div class="css-9vp29i"><img alt="Search engine with automatic tag recommendation" src="/showcase/images/2023/112/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Search engine with automatic tag recommendation</p><p class="chakra-text css-8uhtka">Pream Pitchapa</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/113-klonsuphap"><div class="css-9vp29i"><img alt="KlonSuphap-LM แต่งกลอนแปด ด้วย GPT-2" src="/showcase/images/2023/113/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">KlonSuphap-LM แต่งกลอนแปด ด้วย GPT-2</p><p class="chakra-text css-8uhtka">Kampanat Yingseree</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/66-drum-note-classification"><div class="css-9vp29i"><img alt="Drum Note Classification" src="/showcase/images/2023/66/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Drum Note Classification</p><p class="chakra-text css-8uhtka">Pataranan Sethpakdee</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/67-rain"><div class="css-9vp29i"><img alt="พรุ้งนี้ฝนจะตกหรือไม่เราช่วยคุณด้ายยย" src="/showcase/images/2023/67/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">พรุ้งนี้ฝนจะตกหรือไม่เราช่วยคุณด้ายยย</p><p class="chakra-text css-8uhtka">Natthawin Taeprasert</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/68-klong-4-assistant"><div class="css-9vp29i"><img alt="Klong 4 Assistant: เช็คฉันทลักษณ์และช่วยแต่งโคลงสี่สุภาพ" src="/showcase/images/2023/68/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Klong 4 Assistant: เช็คฉันทลักษณ์และช่วยแต่งโคลงสี่สุภาพ</p><p class="chakra-text css-8uhtka">Thanravee Kamhaengplon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/69-cl-sort"><div class="css-9vp29i"><img alt="CL_sort เพื่อนช่วยจัดไฟล์ที่คุณตามหา!?" src="/showcase/images/2023/69/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">CL_sort เพื่อนช่วยจัดไฟล์ที่คุณตามหา!?</p><p class="chakra-text css-8uhtka">Surapot Sangasap</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/70-breast-cancer-ultrasound-image-segmentation-using-u"><div class="css-9vp29i"><img alt="Breast Cancer Ultrasound Image Segmentation Using U-Net" src="/showcase/images/2023/70/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Breast Cancer Ultrasound Image Segmentation Using U-Net</p><p class="chakra-text css-8uhtka">Suweeraya Noensai</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/71-check-student-attendance-by-face-detection"><div class="css-9vp29i"><img alt="Check student attendance by face detection" src="/showcase/images/2023/71/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Check student attendance by face detection</p><p class="chakra-text css-8uhtka">Atibodee Kuiprasert</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/72-avocado-ripeness-predictor"><div class="css-9vp29i"><img alt="Avocado Ripeness Predictor" src="/showcase/images/2023/72/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Avocado Ripeness Predictor</p><p class="chakra-text css-8uhtka">Alongkorn Kaewprom</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/73-mediapipe"><div class="css-9vp29i"><img alt="โมเดลการแปลภาษามือไทยด้วย MediaPipe" src="/showcase/images/2023/73/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">โมเดลการแปลภาษามือไทยด้วย MediaPipe</p><p class="chakra-text css-8uhtka">Arucha Khematharonon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/75-cloud-classy"><div class="css-9vp29i"><img alt="Cloud Classy ระบบแยกประเภทของเมฆ" src="/showcase/images/2023/75/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Cloud Classy ระบบแยกประเภทของเมฆ</p><p class="chakra-text css-8uhtka">Thanutham Supphaphon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/77-bulletbrief-make-videos-brief-with-bullet-points"><div class="css-9vp29i"><img alt="BulletBrief — Make videos brief with bullet points" src="/showcase/images/2023/77/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">BulletBrief — Make videos brief with bullet points</p><p class="chakra-text css-8uhtka">Darakarn Limkool</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/78-sitting-posture-estimate"><div class="css-9vp29i"><img alt="Sitting Posture Estimate" src="/showcase/images/2023/78/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Sitting Posture Estimate</p><p class="chakra-text css-8uhtka">Aritat Suriyapattanapong</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/79-how-to-know-percent-your-sound?"><div class="css-9vp29i"><img alt="How to know percent your sound?" src="/showcase/images/2023/79/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">How to know percent your sound?</p><p class="chakra-text css-8uhtka">Pittinan Wettayanon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/80-diabetic-foot-ulcers-classification-by-using-planter-foot-thermogram-with-vision-transformer"><div class="css-9vp29i"><img alt="Diabetic Foot Ulcers Classification by using planter foot Thermogram with Vision Transformer (ViT)" src="/showcase/images/2023/80/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Diabetic Foot Ulcers Classification by using planter foot Thermogram with Vision Transformer (ViT)</p><p class="chakra-text css-8uhtka">Picha Jetsadapattarakul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/81-pseudobulbar-palsy-detection-with-wav2vec2-and-openai-whisper"><div class="css-9vp29i"><img alt="Pseudobulbar Palsy Detection with Wav2Vec2 and OpenAI Whisper" src="/showcase/images/2023/81/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Pseudobulbar Palsy Detection with Wav2Vec2 and OpenAI Whisper</p><p class="chakra-text css-8uhtka">Jirat Chiaranaipanich/มัธยมศึกษาปีที่ 4.0</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/82-manga-recommendation"><div class="css-9vp29i"><img alt="Manga Recommendation" src="/showcase/images/2023/82/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Manga Recommendation</p><p class="chakra-text css-8uhtka">Jenta Wonglertsakul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/83-woodsight"><div class="css-9vp29i"><img alt="WoodSight" src="/showcase/images/2023/83/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">WoodSight</p><p class="chakra-text css-8uhtka">Chetphisuth Tongpa</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/84-mini-ai-doctor"><div class="css-9vp29i"><img alt="Mini AI Doctor: Disease Prediction" src="/showcase/images/2023/84/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Mini AI Doctor: Disease Prediction</p><p class="chakra-text css-8uhtka">Kornrawee Kochtat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/85-conversation-generation"><div class="css-9vp29i"><img alt="conversation generation" src="/showcase/images/2023/85/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">conversation generation</p><p class="chakra-text css-8uhtka">Krittiwit Kampradam</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/87-artipost-the-poster-generator-ai"><div class="css-9vp29i"><img alt="ArtiPost: The Poster Generator AI" src="/showcase/images/2023/87/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">ArtiPost: The Poster Generator AI</p><p class="chakra-text css-8uhtka">Pannatat Pipopkullaporn</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/89-pm2.5-time-series-forecasting"><div class="css-9vp29i"><img alt="PM2.5 Time Series Forecasting" src="/showcase/images/2023/89/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">PM2.5 Time Series Forecasting</p><p class="chakra-text css-8uhtka">Natthawee Naewkumpol</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/91-t2e-vocabulary-exam-generator"><div class="css-9vp29i"><img alt="T2E Vocabulary Exam Generator" src="/showcase/images/2023/91/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">T2E Vocabulary Exam Generator</p><p class="chakra-text css-8uhtka">Nutnornont Chamadol</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/92-ai-checker"><div class="css-9vp29i"><img alt="AI หมากฮอสสากล" src="/showcase/images/2023/92/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AI หมากฮอสสากล</p><p class="chakra-text css-8uhtka">Nutdanai Jaratwiboonkul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/93-dog-breed-classification"><div class="css-9vp29i"><img alt="Dog Breed Classification" src="/showcase/images/2023/93/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Dog Breed Classification</p><p class="chakra-text css-8uhtka">Pakin Olanraktham</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/94-text2tags"><div class="css-9vp29i"><img alt="Text2Tags" src="/showcase/images/2023/94/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Text2Tags</p><p class="chakra-text css-8uhtka">Pantai Suyasri</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/95-teeor"><div class="css-9vp29i"><img alt="TEEOR" src="/showcase/images/2023/95/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TEEOR</p><p class="chakra-text css-8uhtka">Pataradanai Akkratch</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/96-catsification"><div class="css-9vp29i"><img alt="CATsification" src="/showcase/images/2023/96/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">CATsification</p><p class="chakra-text css-8uhtka">Pawinthawat Chandravat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/97-ai-fallingasleepdriving"><div class="css-9vp29i"><img alt="AI FallingAsleepDriving (AI ตรวจสอบผู้ขับขี่หลับใน)" src="/showcase/images/2023/97/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AI FallingAsleepDriving (AI ตรวจสอบผู้ขับขี่หลับใน)</p><p class="chakra-text css-8uhtka">Puratsakorn Kietnonthapat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/98-virtual-coding-mentor"><div class="css-9vp29i"><img alt="Virtual Coding Mentor" src="/showcase/images/2023/98/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Virtual Coding Mentor</p><p class="chakra-text css-8uhtka">Pipatpong Chuchuai</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/99-phish-off"><div class="css-9vp29i"><img alt="Phish-Off" src="/showcase/images/2023/99/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Phish-Off</p><p class="chakra-text css-8uhtka">Plengpin Tongdon-Ngao</p></div></div></a></div></div></div><div tabindex="0" aria-labelledby="tabs-1--tab-2" role="tabpanel" hidden="" id="tabs-1--tabpanel-2" class="chakra-tabs__tab-panel css-a5mhaz"><div class="css-bcb7hj"><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/A-Lip-Reader"><div class="css-9vp29i"><img alt="A Lip Reader" src="/showcase/images/2022/53/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">A Lip Reader</p><p class="chakra-text css-8uhtka">พุทธคุณ บุญชัย (ข้าวตู)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/AI-%E0%B9%81%E0%B8%A2%E0%B8%81%E0%B9%81%E0%B8%A2%E0%B8%B0%E0%B9%81%E0%B8%A1%E0%B8%87%E0%B8%94%E0%B8%B2%E0%B8%88%E0%B8%B2%E0%B8%99-%E0%B8%81%E0%B8%B1%E0%B8%9A-%E0%B9%81%E0%B8%A1%E0%B8%87%E0%B8%94%E0%B8%B2%E0%B8%96%E0%B9%89%E0%B8%A7%E0%B8%A2"><div class="css-9vp29i"><img alt="AI แยกแยะแมงดาจาน กับ แมงดาถ้วย" src="/showcase/images/2022/39/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AI แยกแยะแมงดาจาน กับ แมงดาถ้วย</p><p class="chakra-text css-8uhtka">ภัคพล อาจบุราย (หลุยส์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/American-Sign-Language"><div class="css-9vp29i"><img alt="American Sign Language" src="/showcase/images/2022/52/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">American Sign Language</p><p class="chakra-text css-8uhtka">กรกมล แสงสว่าง (เบลล์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Auto-Lyric-Recognizer"><div class="css-9vp29i"><img alt="Auto Lyric Recognizer" src="/showcase/images/2022/28/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Auto Lyric Recognizer</p><p class="chakra-text css-8uhtka">กิตติพงศ์ เทพอยู่ (ปืน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Automatic-E2E-Thai-Question-Generation-with-MT5"><div class="css-9vp29i"><img alt="Automatic E2E Thai Question Generation with MT5" src="/showcase/images/2022/62/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Automatic E2E Thai Question Generation with MT5</p><p class="chakra-text css-8uhtka">ปรินทพัฒน์ เพ็งพันธุ์ (ปริน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/BACK-(Blind-All-Can-Know)---Action-Captioning-for-Blinds"><div class="css-9vp29i"><img alt="BACK (Blind All Can Know) - Action Captioning for Blinds" src="/showcase/images/2022/21/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">BACK (Blind All Can Know) - Action Captioning for Blinds</p><p class="chakra-text css-8uhtka">โชติวัฒน์ ตั้งสถาพร (ไนน์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Brain-Tumor-Segmentation-using-SegResNet"><div class="css-9vp29i"><img alt="Brain Tumor Segmentation using SegResNet" src="/showcase/images/2022/43/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Brain Tumor Segmentation using SegResNet</p><p class="chakra-text css-8uhtka">ณัฐวดี ลีภัทรกิจ (กิ่งแก้ว)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Cactus-Classification-with-Fastai"><div class="css-9vp29i"><img alt="Cactus Classification with Fastai" src="/showcase/images/2022/24/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Cactus Classification with Fastai</p><p class="chakra-text css-8uhtka">ปัณณธร กรุดทอง (โฟกัส)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram"><div class="css-9vp29i"><img alt="Chaos EDM: Generating EDM Song with VAE (Variational Autoencoder) Spectrogram" src="/showcase/images/2022/34/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Chaos EDM: Generating EDM Song with VAE (Variational Autoencoder) Spectrogram</p><p class="chakra-text css-8uhtka">ณยศ สุวัฒโน (ไมค์กี้)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Classical-Music-Generator"><div class="css-9vp29i"><img alt="Classical Music Generator" src="/showcase/images/2022/44/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Classical Music Generator</p><p class="chakra-text css-8uhtka">มณิสรา แซ่จัน (ฟิล์ม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Crossec--%E0%B8%A3%E0%B8%B0%E0%B8%9A%E0%B8%9A%E0%B8%AA%E0%B9%88%E0%B8%87%E0%B9%80%E0%B8%AA%E0%B8%A3%E0%B8%B4%E0%B8%A1%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%97%E0%B8%B3%E0%B8%9B%E0%B8%8F%E0%B8%B4%E0%B8%9A%E0%B8%B1%E0%B8%95%E0%B8%B4%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B9%80%E0%B8%99%E0%B8%B7%E0%B9%89%E0%B8%AD%E0%B9%80%E0%B8%A2%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B8%9E%E0%B8%B7%E0%B8%8A%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2%E0%B8%9B%E0%B8%B1%E0%B8%8D%E0%B8%8D%E0%B8%B2%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B8%94%E0%B8%B4%E0%B8%A9%E0%B8%90%E0%B9%8C"><div class="css-9vp29i"><img alt="Crossec : ระบบส่งเสริมการทำปฏิบัติการเนื้อเยื่อพืชด้วยปัญญาประดิษฐ์" src="/showcase/images/2022/51/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Crossec : ระบบส่งเสริมการทำปฏิบัติการเนื้อเยื่อพืชด้วยปัญญาประดิษฐ์</p><p class="chakra-text css-8uhtka">วิทวัส กิติภัทร์ถาวร (เอิร์ธ)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Debunker-ML-%E0%B8%95%E0%B8%A3%E0%B8%A7%E0%B8%88%E0%B8%88%E0%B8%B1%E0%B8%9A%E0%B8%82%E0%B9%88%E0%B8%B2%E0%B8%A7%E0%B8%A5%E0%B8%A7%E0%B8%87"><div class="css-9vp29i"><img alt="Debunker: ML ตรวจจับข่าวลวง" src="/showcase/images/2022/42/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Debunker: ML ตรวจจับข่าวลวง</p><p class="chakra-text css-8uhtka">นิธิวัฒน์ สิริรัตนชัยกุล (ตง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model"><div class="css-9vp29i"><img alt="Detect and collect COVID-19 data more faster by using ATK-OCR Classification (AOC) model" src="/showcase/images/2022/55/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Detect and collect COVID-19 data more faster by using ATK-OCR Classification (AOC) model</p><p class="chakra-text css-8uhtka">ธนอนันท์ เฉลิมพันธ์ (เอ็ม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Edge-to-Face-Drawing-Realistic-Faces-from-Canny-Edges"><div class="css-9vp29i"><img alt="Edge-to-Face: Drawing Realistic Faces from Canny Edges" src="/showcase/images/2022/26/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Edge-to-Face: Drawing Realistic Faces from Canny Edges</p><p class="chakra-text css-8uhtka">นิธิศรัฎฐ์ พุฒิภาพงศ์ (พลัส)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Emotion-Detection-from-Facial-Micro-experessions"><div class="css-9vp29i"><img alt="Emotion Detection from Facial Micro-experessions" src="/showcase/images/2022/61/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Emotion Detection from Facial Micro-experessions</p><p class="chakra-text css-8uhtka">ครองภพ มั่นคง (ไบรท์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Fake-Product-Detection-on-Online-Retail"><div class="css-9vp29i"><img alt="Fake Product Detection on Online Retail" src="/showcase/images/2022/23/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Fake Product Detection on Online Retail</p><p class="chakra-text css-8uhtka">เจษฎา ปราณี (แจ็ค)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Find-Water-from-Satellite-Images-Using-U-Net-Image-Segmentation-with-Pytorch"><div class="css-9vp29i"><img alt="Find Water from Satellite Images Using U-Net Image Segmentation with Pytorch" src="/showcase/images/2022/60/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Find Water from Satellite Images Using U-Net Image Segmentation with Pytorch</p><p class="chakra-text css-8uhtka">วรกาญจน์ ลาสุดี (ปีใหม่)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Food-Ingredients-Label-Reader-for-Food-Allergy"><div class="css-9vp29i"><img alt="Food Ingredients Label Reader for Food Allergy" src="/showcase/images/2022/25/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Food Ingredients Label Reader for Food Allergy</p><p class="chakra-text css-8uhtka">พีรณัฐ เมฆวิศิษฏ์ (ปอนด์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Game-Recommendation-by-using-Neural-Network-Embeddings"><div class="css-9vp29i"><img alt="Game Recommendation by using Neural Network Embeddings" src="/showcase/images/2022/33/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Game Recommendation by using Neural Network Embeddings</p><p class="chakra-text css-8uhtka">มาวิน ศรีชาติ (วิน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/GANime-FullBody-%E0%B8%A7%E0%B8%B2%E0%B8%94%E0%B8%A3%E0%B8%B9%E0%B8%9B%E0%B8%95%E0%B8%B1%E0%B8%A7%E0%B8%A5%E0%B8%B0%E0%B8%84%E0%B8%A3%E0%B8%AD%E0%B8%99%E0%B8%B4%E0%B9%80%E0%B8%A1%E0%B8%B0(%E0%B8%AA%E0%B8%B2%E0%B8%A7%E0%B9%86)%E0%B9%81%E0%B8%9A%E0%B8%9A%E0%B9%80%E0%B8%95%E0%B9%87%E0%B8%A1%E0%B8%95%E0%B8%B1%E0%B8%A7-%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-Deep-Learning"><div class="css-9vp29i"><img alt="GANime-FullBody วาดรูปตัวละครอนิเมะ(สาวๆ)แบบเต็มตัว ด้วย Deep Learning" src="/showcase/images/2022/59/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">GANime-FullBody วาดรูปตัวละครอนิเมะ(สาวๆ)แบบเต็มตัว ด้วย Deep Learning</p><p class="chakra-text css-8uhtka">หิรัญกุล พิมพ์ศิริ (ไกด์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Garbage-Detection-with-Tensorflow-Lite"><div class="css-9vp29i"><img alt="Garbage Detection with Tensorflow Lite" src="/showcase/images/2022/36/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Garbage Detection with Tensorflow Lite</p><p class="chakra-text css-8uhtka">กันต์พัจน์ วิเศษสุข (กัน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Image-Transfer-Day-to-Night-and-Night-to-Day"><div class="css-9vp29i"><img alt="Image Transfer Day-to-Night and Night-to-Day" src="/showcase/images/2022/29/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Image Transfer Day-to-Night and Night-to-Day</p><p class="chakra-text css-8uhtka">ณฐกร คเชนทร (เท็น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Is-that-a-Supra"><div class="css-9vp29i"><img alt="Is that a Supra?!" src="/showcase/images/2022/40/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Is that a Supra?!</p><p class="chakra-text css-8uhtka">จิตรบุณย์ ทรัพย์สินทวีลาภ (กั๊ต)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Lamiaceae-Classification-%E0%B9%81%E0%B8%A2%E0%B8%81%E0%B8%9E%E0%B8%B7%E0%B8%8A%E0%B8%A7%E0%B8%87%E0%B8%A8%E0%B9%8C%E0%B8%81%E0%B8%B0%E0%B9%80%E0%B8%9E%E0%B8%A3%E0%B8%B2-3-%E0%B8%8A%E0%B8%99%E0%B8%B4%E0%B8%94"><div class="css-9vp29i"><img alt="Lamiaceae Classification แยกพืชวงศ์กะเพรา 3 ชนิด" src="/showcase/images/2022/45/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Lamiaceae Classification แยกพืชวงศ์กะเพรา 3 ชนิด</p><p class="chakra-text css-8uhtka">วชิรวิทย์ ไชยมาตย์ (เจ้านาย)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Learn-Chinese-Faster-by-Using-Handwritten-Chinese-Character-Recognition-(HCCR)"><div class="css-9vp29i"><img alt="Learn Chinese Faster by Using Handwritten Chinese Character Recognition (HCCR)" src="/showcase/images/2022/50/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Learn Chinese Faster by Using Handwritten Chinese Character Recognition (HCCR)</p><p class="chakra-text css-8uhtka">ภควุฒิ ธรรมาวุฒิกุล (Army)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Microplastic-detection-and-collect-statistical-tebular-data."><div class="css-9vp29i"><img alt="Microplastic detection and collect statistical tebular data." src="/showcase/images/2022/41/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Microplastic detection and collect statistical tebular data.</p><p class="chakra-text css-8uhtka">ภานุวัฒน์ วงศ์พัฒนวุฒิ (ก้อง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Music-Recognition"><div class="css-9vp29i"><img alt="Music Recognition" src="/showcase/images/2022/30/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Music Recognition</p><p class="chakra-text css-8uhtka">นนทพรรษ วงษ์กัณหา (นน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/My-Little-HR-%E0%B9%82%E0%B8%A1%E0%B9%80%E0%B8%94%E0%B8%A5%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B9%80%E0%B8%A1%E0%B8%B4%E0%B8%99%E0%B9%80%E0%B8%87%E0%B8%B4%E0%B8%99%E0%B9%80%E0%B8%94%E0%B8%B7%E0%B8%AD%E0%B8%99%E0%B8%AD%E0%B8%B2%E0%B8%8A%E0%B8%B5%E0%B8%9E%E0%B8%AA%E0%B8%B2%E0%B8%A2-IT-%E0%B9%83%E0%B8%99%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B9%80%E0%B8%97%E0%B8%A8%E0%B9%84%E0%B8%97%E0%B8%A2"><div class="css-9vp29i"><img alt="My Little HR: โมเดลประเมินเงินเดือนอาชีพสาย IT ในประเทศไทย" src="/showcase/images/2022/58/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">My Little HR: โมเดลประเมินเงินเดือนอาชีพสาย IT ในประเทศไทย</p><p class="chakra-text css-8uhtka">กันตพงศ์ วงศ์พานิชย์ (เติร์ด)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/NLP-for-genre-predictions-on-FFnet-an-antithesis-to-utilitarianism"><div class="css-9vp29i"><img alt="NLP for genre predictions on FFnet: an antithesis to utilitarianism" src="/showcase/images/2022/38/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">NLP for genre predictions on FFnet: an antithesis to utilitarianism</p><p class="chakra-text css-8uhtka">zeiosis@</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Object-Detection-in-White-Blood-Cells-for-Leukemia"><div class="css-9vp29i"><img alt="Object Detection in White Blood Cells for Leukemia" src="/showcase/images/2022/64/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Object Detection in White Blood Cells for Leukemia</p><p class="chakra-text css-8uhtka">แพรวา ชูบ้านนา (แพรว)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Obstacle-Detection-for-Blind-people-%E0%B8%8A%E0%B9%88%E0%B8%A7%E0%B8%A2%E0%B9%80%E0%B8%AB%E0%B8%A5%E0%B8%B7%E0%B8%AD%E0%B8%9C%E0%B8%B9%E0%B9%89%E0%B8%9E%E0%B8%B4%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%97%E0%B8%B2%E0%B8%87%E0%B8%AA%E0%B8%B2%E0%B8%A2%E0%B8%95%E0%B8%B2%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-Deep-Learning"><div class="css-9vp29i"><img alt="Obstacle Detection for Blind people ช่วยเหลือผู้พิการทางสายตาด้วย Deep Learning" src="/showcase/images/2022/54/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Obstacle Detection for Blind people ช่วยเหลือผู้พิการทางสายตาด้วย Deep Learning</p><p class="chakra-text css-8uhtka">เทพบดินทร์ ใจอินสม (ฟู่)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Plant-Disease-Classification"><div class="css-9vp29i"><img alt="Plant Disease Classification" src="/showcase/images/2022/47/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Plant Disease Classification</p><p class="chakra-text css-8uhtka">รัชชานนท์ มุขแก้ว (นนท์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide"><div class="css-9vp29i"><img alt="PsychNLP: A BERT-based NLP model as a screening tool to help classify the risks of depression and suicide" src="/showcase/images/2022/57/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">PsychNLP: A BERT-based NLP model as a screening tool to help classify the risks of depression and suicide</p><p class="chakra-text css-8uhtka">พลกฤต สาตสิน (เจ)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/RL-in-Traffic-Management"><div class="css-9vp29i"><img alt="RL in Traffic Management" src="/showcase/images/2022/49/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">RL in Traffic Management</p><p class="chakra-text css-8uhtka">ณดล พิพัฒนติกานันท์ (ไตตั้น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Sick-Pig-Classifier"><div class="css-9vp29i"><img alt="Sick Pig Classifier" src="/showcase/images/2022/37/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Sick Pig Classifier</p><p class="chakra-text css-8uhtka">ภวัต ลีชาแสน (บีม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Single-Note-Music-Classification"><div class="css-9vp29i"><img alt="Single Note Music Classification" src="/showcase/images/2022/65/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Single Note Music Classification</p><p class="chakra-text css-8uhtka">ณภัทร เสรีรักษ์ (นีร)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Text-to-image-synthesis-with-VQGAN-ThCLIP"><div class="css-9vp29i"><img alt="Text-to-image synthesis with VQGAN-ThCLIP" src="/showcase/images/2022/32/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Text-to-image synthesis with VQGAN-ThCLIP</p><p class="chakra-text css-8uhtka">ภูริช ศิริทิพย์ (มาร์ค)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/TextDoe-%E0%B9%82%E0%B8%A1%E0%B9%80%E0%B8%94%E0%B8%A5%E0%B8%88%E0%B8%B3%E0%B9%81%E0%B8%99%E0%B8%81%E0%B9%81%E0%B8%A7%E0%B8%94%E0%B8%A7%E0%B8%87%E0%B8%9A%E0%B8%97%E0%B8%84%E0%B8%A7%E0%B8%B2%E0%B8%A1%E0%B8%AA%E0%B8%B4%E0%B9%88%E0%B8%87%E0%B8%9E%E0%B8%B4%E0%B8%A1%E0%B8%9E%E0%B9%8C"><div class="css-9vp29i"><img alt="TextDoe: โมเดลจำแนกแวดวงบทความสิ่งพิมพ์" src="/showcase/images/2022/27/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TextDoe: โมเดลจำแนกแวดวงบทความสิ่งพิมพ์</p><p class="chakra-text css-8uhtka">โชติอนันต์ทรัพย์ โสภาเคน (โชกุน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/TLDR;-Terms-and-Conditions-Summarizer"><div class="css-9vp29i"><img alt="TLDR; Terms and Conditions Summarizer" src="/showcase/images/2022/48/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TLDR; Terms and Conditions Summarizer</p><p class="chakra-text css-8uhtka">ศุภโชค บุตรดีขันธ์ (บูม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Using-Machine-Learning-to-create-Auto-Pitch-Writer-for-UTAU"><div class="css-9vp29i"><img alt="Using Machine Learning to create Auto Pitch Writer for UTAU" src="/showcase/images/2022/63/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Using Machine Learning to create Auto Pitch Writer for UTAU</p><p class="chakra-text css-8uhtka">จิรา กุลจิราพงษ์ (จิรา)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Violence-Detection"><div class="css-9vp29i"><img alt="Violence Detection" src="/showcase/images/2022/22/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Violence Detection</p><p class="chakra-text css-8uhtka">ชินวัตร นาไชยธง (ม่อน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/vTranslator-Transcribe-and-Translate-VTuber-using-Wav2Vec2"><div class="css-9vp29i"><img alt="vTranslator: Transcribe and Translate VTuber using Wav2Vec2" src="/showcase/images/2022/31/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">vTranslator: Transcribe and Translate VTuber using Wav2Vec2</p><p class="chakra-text css-8uhtka">ธนภณ ทองจำนงค์ (ธันย์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/WanchanBERTa-Thai-Grammarly"><div class="css-9vp29i"><img alt="WanchanBERTa Thai Grammarly" src="/showcase/images/2022/35/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">WanchanBERTa Thai Grammarly</p><p class="chakra-text css-8uhtka">อิทธิพัฒน์ ปานขำ (มาร์จิ้น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/%E0%B9%82%E0%B8%A1%E0%B9%80%E0%B8%94%E0%B8%A5-CNN-%E0%B8%AA%E0%B8%B3%E0%B8%AB%E0%B8%A3%E0%B8%B1%E0%B8%9A%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%88%E0%B8%B3%E0%B9%81%E0%B8%99%E0%B8%81%E0%B8%AA%E0%B8%B1%E0%B8%8D%E0%B8%8D%E0%B8%B2%E0%B8%93%E0%B8%AA%E0%B8%A1%E0%B8%AD%E0%B8%87%E0%B9%83%E0%B8%99%E0%B8%A3%E0%B8%B0%E0%B8%9A%E0%B8%9A-SSVEP-BCI-%E0%B8%AA%E0%B8%B3%E0%B8%AB%E0%B8%A3%E0%B8%B1%E0%B8%9A%E0%B9%84%E0%B8%A1%E0%B9%80%E0%B8%81%E0%B8%A3%E0%B8%99-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine)"><div class="css-9vp29i"><img alt="โมเดล CNN สำหรับการจำแนกสัญญาณสมองในระบบ SSVEP-BCI สำหรับไมเกรน (A CNN for Classification Task in SSVEP-BCI for Migraine)" src="/showcase/images/2022/56/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">โมเดล CNN สำหรับการจำแนกสัญญาณสมองในระบบ SSVEP-BCI สำหรับไมเกรน (A CNN for Classification Task in SSVEP-BCI for Migraine)</p><p class="chakra-text css-8uhtka">ฆนัท บุญจง (เค)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/%E0%B8%AA%E0%B8%A3%E0%B9%89%E0%B8%B2%E0%B8%87%E0%B8%AA%E0%B8%A3%E0%B8%A3%E0%B8%9A%E0%B8%97%E0%B9%80%E0%B8%9E%E0%B8%A5%E0%B8%87-Undertale-%E0%B8%9C%E0%B9%88%E0%B8%B2%E0%B8%99-LSTM-%E0%B9%81%E0%B8%A5%E0%B8%B0-Teacher-Forcing-RNN"><div class="css-9vp29i"><img alt="สร้างสรรบทเพลง Undertale ผ่าน LSTM และ Teacher Forcing RNN" src="/showcase/images/2022/46/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">สร้างสรรบทเพลง Undertale ผ่าน LSTM และ Teacher Forcing RNN</p><p class="chakra-text css-8uhtka">นพวิทย์ ตันติศิริวัฒน์ (ภีม)</p></div></div></a></div></div></div><div tabindex="0" aria-labelledby="tabs-1--tab-3" role="tabpanel" hidden="" id="tabs-1--tabpanel-3" class="chakra-tabs__tab-panel css-a5mhaz"><div class="css-bcb7hj"><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/001-foody-dudy"><div class="css-9vp29i"><img alt="FoodyDudy" src="/showcase/images/2021/001/1.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">FoodyDudy</p><p class="chakra-text css-8uhtka">Phacharaphol Somboontham (Gemmy)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle"><div class="css-9vp29i"><img alt="LiDAR 3D Point Cloud Object Detection for Autonomous Vehicle" src="/showcase/images/2021/002/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">LiDAR 3D Point Cloud Object Detection for Autonomous Vehicle</p><p class="chakra-text css-8uhtka">Thanapat Chotipun (Patrick)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/003-Lalita-Chinese-Thai-Machine-Translation"><div class="css-9vp29i"><img alt="Lalita Chinese-Thai Machine Translation " src="/showcase/images/2021/003/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Lalita Chinese-Thai Machine Translation </p><p class="chakra-text css-8uhtka">Lalita Deelert (Looktarn)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/004-%E0%B9%81%E0%B8%99%E0%B8%B0%E0%B8%99%E0%B8%B3%E0%B8%A3%E0%B8%B2%E0%B8%84%E0%B8%B2%E0%B8%A3%E0%B8%B9%E0%B8%9B%E0%B8%84%E0%B8%AD%E0%B8%A1%E0%B8%A1%E0%B8%B4%E0%B8%8A%E0%B8%8A%E0%B8%B1%E0%B8%99%E0%B8%AD%E0%B8%99%E0%B8%B4%E0%B9%80%E0%B8%A1%E0%B8%B0%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-machine-learning-%E0%B9%82%E0%B8%94%E0%B8%A2-fastai"><div class="css-9vp29i"><img alt="แนะนำราคารูปคอมมิชชันอนิเมะด้วย machine learning โดย fastai" src="/showcase/images/2021/004/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">แนะนำราคารูปคอมมิชชันอนิเมะด้วย machine learning โดย fastai</p><p class="chakra-text css-8uhtka">Prad Rattanakijsoonthorn (BB)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/005-Thai-Text-to-Speech-with-Tacotron"><div class="css-9vp29i"><img alt="Thai Text-to-Speech with Tacotron" src="/showcase/images/2021/005/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Thai Text-to-Speech with Tacotron</p><p class="chakra-text css-8uhtka">Rajasurang Wongkrasaemongkol (Prim)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/006-Salmon-Classifier-%E0%B9%80%E0%B8%A3%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B8%87%E0%B8%A7%E0%B8%B8%E0%B9%88%E0%B8%99%E0%B9%86%E0%B8%82%E0%B8%AD%E0%B8%87%E0%B8%9B%E0%B8%A5%E0%B8%B2%E0%B9%81%E0%B8%8B%E0%B8%A5%E0%B8%A1%E0%B8%AD%E0%B8%99"><div class="css-9vp29i"><img alt="Salmon Classifier: เรื่องวุ่นๆของปลาแซลมอน" src="/showcase/images/2021/006/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Salmon Classifier: เรื่องวุ่นๆของปลาแซลมอน</p><p class="chakra-text css-8uhtka">Tanakrit Saiphan (Mookrob)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/007-Thai-Music-Generation-with-VAE"><div class="css-9vp29i"><img alt="Thai Music (Ranat Ek) Generation with Variational Autoencoder" src="/showcase/images/2021/007/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Thai Music (Ranat Ek) Generation with Variational Autoencoder</p><p class="chakra-text css-8uhtka">Noppawat Tantisiriwat (Rew)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/008-Itinerary-Creator-%E0%B9%82%E0%B8%9B%E0%B8%A3%E0%B9%81%E0%B8%81%E0%B8%A3%E0%B8%A1%E0%B8%8A%E0%B9%88%E0%B8%A7%E0%B8%A2%E0%B8%A7%E0%B8%B2%E0%B8%87%E0%B9%81%E0%B8%9C%E0%B8%99%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B9%80%E0%B8%97%E0%B8%B5%E0%B9%88%E0%B8%A2%E0%B8%A7%E0%B9%83%E0%B8%AB%E0%B9%89%E0%B9%83%E0%B8%81%E0%B8%A5%E0%B9%89%E0%B9%80%E0%B8%84%E0%B8%B5%E0%B8%A2%E0%B8%87%E0%B8%81%E0%B8%B1%E0%B8%9A%E0%B8%84%E0%B8%A7%E0%B8%B2%E0%B8%A1%E0%B8%8A%E0%B8%AD%E0%B8%9A%E0%B8%82%E0%B8%AD%E0%B8%87%E0%B9%80%E0%B8%A3%E0%B8%B2"><div class="css-9vp29i"><img alt="Itinerary Creator โปรแกรมช่วยวางแผนการเที่ยวให้ใกล้เคียงกับความชอบของเรา" src="/showcase/images/2021/008/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Itinerary Creator โปรแกรมช่วยวางแผนการเที่ยวให้ใกล้เคียงกับความชอบของเรา</p><p class="chakra-text css-8uhtka">Jullawat Sinsiri (Nano)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/009-Finger-Movement-Classification-from-Electromyography"><div class="css-9vp29i"><img alt="Finger Movement Classification from Electromyography" src="/showcase/images/2021/009/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Finger Movement Classification from Electromyography</p><p class="chakra-text css-8uhtka">Raya Sakashita Worasawate (Raya)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/010-%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%A3%E0%B8%B9%E0%B9%89%E0%B8%88%E0%B8%B3%E0%B8%AD%E0%B8%B2%E0%B8%A3%E0%B8%A1%E0%B8%93%E0%B9%8C%E0%B9%80%E0%B8%AA%E0%B8%B5%E0%B8%A2%E0%B8%87%E0%B8%9E%E0%B8%B9%E0%B8%94%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-ThaiserDataset"><div class="css-9vp29i"><img alt="การรู้จำอารมณ์เสียงพูดด้วย ThaiserDataset" src="/showcase/images/2021/010/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">การรู้จำอารมณ์เสียงพูดด้วย ThaiserDataset</p><p class="chakra-text css-8uhtka">Pongsakon Kaewjaidee (Oak)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/011-%E0%B9%81%E0%B8%9A%E0%B8%9A%E0%B8%88%E0%B8%B3%E0%B8%A5%E0%B8%AD%E0%B8%87%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%97%E0%B8%B3%E0%B8%99%E0%B8%B2%E0%B8%A2%E0%B8%9C%E0%B8%A5%E0%B8%9C%E0%B8%A5%E0%B8%B4%E0%B8%95%E0%B8%82%E0%B8%AD%E0%B8%87%E0%B8%9E%E0%B8%B7%E0%B8%8A%E0%B9%80%E0%B8%A8%E0%B8%A3%E0%B8%A9%E0%B8%90%E0%B8%81%E0%B8%B4%E0%B8%88-%E0%B9%82%E0%B8%94%E0%B8%A2%E0%B9%83%E0%B8%8A%E0%B9%89%E0%B9%80%E0%B8%97%E0%B8%84%E0%B8%99%E0%B8%B4%E0%B8%84-Machine-Learning"><div class="css-9vp29i"><img alt="แบบจำลองการทำนายผลผลิตของพืชเศรษฐกิจ โดยใช้เทคนิค Machine Learning" src="/showcase/images/2021/011/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">แบบจำลองการทำนายผลผลิตของพืชเศรษฐกิจ โดยใช้เทคนิค Machine Learning</p><p class="chakra-text css-8uhtka">Sooknapat Chongsawadvoarkul (NunNun)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" 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0 0 1px rgba(0, 0, 0, 0.05);--chakra-shadows-sm:0 1px 2px 0 rgba(0, 0, 0, 0.05);--chakra-shadows-base:0 1px 3px 0 rgba(0, 0, 0, 0.1),0 1px 2px 0 rgba(0, 0, 0, 0.06);--chakra-shadows-md:0 4px 6px -1px rgba(0, 0, 0, 0.1),0 2px 4px -1px rgba(0, 0, 0, 0.06);--chakra-shadows-lg:0 10px 15px -3px rgba(0, 0, 0, 0.1),0 4px 6px -2px rgba(0, 0, 0, 0.05);--chakra-shadows-xl:0 20px 25px -5px rgba(0, 0, 0, 0.1),0 10px 10px -5px rgba(0, 0, 0, 0.04);--chakra-shadows-2xl:0 25px 50px -12px rgba(0, 0, 0, 0.25);--chakra-shadows-outline:0 0 0 3px rgba(66, 153, 225, 0.6);--chakra-shadows-inner:inset 0 2px 4px 0 rgba(0,0,0,0.06);--chakra-shadows-none:none;--chakra-shadows-dark-lg:rgba(0, 0, 0, 0.1) 0px 0px 0px 1px,rgba(0, 0, 0, 0.2) 0px 5px 10px,rgba(0, 0, 0, 0.4) 0px 15px 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1fh9ko">.css-1fh9ko{color:var(--chakra-colors-gray-50);font-weight:var(--chakra-fontWeights-bold);font-size:90%;width:100%;height:62.5px;background-color:var(--chakra-colors-blackAlpha-300);-webkit-padding-start:var(--chakra-space-4);padding-inline-start:var(--chakra-space-4);-webkit-padding-end:var(--chakra-space-4);padding-inline-end:var(--chakra-space-4);padding-top:var(--chakra-space-2);padding-bottom:var(--chakra-space-2);}</style><div class="css-1fh9ko"><div class="css-0"><style data-emotion="css 8uhtka">.css-8uhtka{overflow:hidden;text-overflow:ellipsis;white-space:nowrap;}</style><p class="chakra-text css-8uhtka">Color Harmony Classifier ML (CoHaML)</p><p class="chakra-text css-8uhtka">ปภาดา แสงปรีดีกรณ์(หมูแดง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2024/10-chonlana-kruawuthikun"><div class="css-9vp29i"><img alt="Aquarium Fish Species Classification - โมเดลระบุสปีชีส์สัตว์น้ำจากภาพ" 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css-8uhtka">Crop Recommendation System for Thai Economic Plants</p><p class="chakra-text css-8uhtka">ณัฐวีณ์ สุนิตย์สกุล( ตัง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2024/4-sittipark-kaewka"><div class="css-9vp29i"><img alt="Spider Classification" src="/showcase/images/2024/4/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Spider Classification</p><p class="chakra-text css-8uhtka">สิทธิภาคย์ แก้วกา(ไออุ่น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2024/5-nontapat-auetrongjit"><div class="css-9vp29i"><img alt="Student Behavior Detector in Classroom" src="/showcase/images/2024/5/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Student Behavior Detector in Classroom</p><p class="chakra-text css-8uhtka">นนทพัทธ์ เอื้อตรงจิตต์(เฟิร์ม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2024/6-thanaphum-saywongin"><div class="css-9vp29i"><img alt="AniRec" src="/showcase/images/2024/6/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AniRec</p><p class="chakra-text css-8uhtka">ธนภูมิ สายวงศ์อินทร์(อิคคิว)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2024/7-guntee-doungmanee"><div class="css-9vp29i"><img alt="Synthesize High-Quality Thai Vector Fonts" src="/showcase/images/2024/7/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Synthesize High-Quality Thai Vector Fonts</p><p class="chakra-text css-8uhtka">กันต์ธีร์ ดวงมณี(พอเพียง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" 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class="css-9vp29i"><img alt="marching-waifu-x: Diffusion models are zero-shot 3D character generators, too" src="/showcase/images/2023/103/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">marching-waifu-x: Diffusion models are zero-shot 3D character generators, too</p><p class="chakra-text css-8uhtka">Tawin Jiramahapokee</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/104-lo-fi-music"><div class="css-9vp29i"><img alt="Lo-Fi music style transfer" src="/showcase/images/2023/104/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Lo-Fi music style transfer</p><p class="chakra-text css-8uhtka">Thanakit Chongwilaikasem/มัธยมศึกษาปีที่ 4.0</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/105-pytorch-thai-food-image-classification"><div class="css-9vp29i"><img alt="Pytorch Thai food image classification" src="/showcase/images/2023/105/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Pytorch Thai food image classification</p><p class="chakra-text css-8uhtka">Saktanuth Praditukrit</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/106-plank-form-checker"><div class="css-9vp29i"><img alt="Plank Form Checker" src="/showcase/images/2023/106/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Plank Form Checker</p><p class="chakra-text css-8uhtka">Thee Kittivorapat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/107-dog-emotions"><div class="css-9vp29i"><img alt="Dog emotions" src="/showcase/images/2023/107/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Dog emotions</p><p class="chakra-text css-8uhtka">Thirada Thomnam</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/109-profanityguard-youtube"><div class="css-9vp29i"><img alt="ProfanityGuard ตรวจจับคำหยาบด้วย AI ก่อนนำไปลง Youtube" src="/showcase/images/2023/109/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">ProfanityGuard ตรวจจับคำหยาบด้วย AI ก่อนนำไปลง Youtube</p><p class="chakra-text css-8uhtka">Pasit Khumsena</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/110-th-en-MT"><div class="css-9vp29i"><img alt="TH-EN Machine Translation" src="/showcase/images/2023/110/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TH-EN Machine Translation</p><p class="chakra-text css-8uhtka">Tarit Witworrasakul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/111-object-detection-for-cctv-with-traffic"><div class="css-9vp29i"><img alt="Object detection for CCTV with traffic" src="/showcase/images/2023/111/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Object detection for CCTV with traffic</p><p class="chakra-text css-8uhtka">Kontuch Suksawat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/112-search-engine-with-automatic-tag-recommendation"><div class="css-9vp29i"><img alt="Search engine with automatic tag recommendation" src="/showcase/images/2023/112/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Search engine with automatic tag recommendation</p><p class="chakra-text css-8uhtka">Pream Pitchapa</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/113-klonsuphap"><div class="css-9vp29i"><img alt="KlonSuphap-LM แต่งกลอนแปด ด้วย GPT-2" src="/showcase/images/2023/113/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">KlonSuphap-LM แต่งกลอนแปด ด้วย GPT-2</p><p class="chakra-text css-8uhtka">Kampanat Yingseree</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/66-drum-note-classification"><div class="css-9vp29i"><img alt="Drum Note Classification" src="/showcase/images/2023/66/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Drum Note Classification</p><p class="chakra-text css-8uhtka">Pataranan Sethpakdee</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/67-rain"><div class="css-9vp29i"><img alt="พรุ้งนี้ฝนจะตกหรือไม่เราช่วยคุณด้ายยย" src="/showcase/images/2023/67/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">พรุ้งนี้ฝนจะตกหรือไม่เราช่วยคุณด้ายยย</p><p class="chakra-text css-8uhtka">Natthawin Taeprasert</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/68-klong-4-assistant"><div class="css-9vp29i"><img alt="Klong 4 Assistant: เช็คฉันทลักษณ์และช่วยแต่งโคลงสี่สุภาพ" src="/showcase/images/2023/68/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Klong 4 Assistant: เช็คฉันทลักษณ์และช่วยแต่งโคลงสี่สุภาพ</p><p class="chakra-text css-8uhtka">Thanravee Kamhaengplon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/69-cl-sort"><div class="css-9vp29i"><img alt="CL_sort เพื่อนช่วยจัดไฟล์ที่คุณตามหา!?" src="/showcase/images/2023/69/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">CL_sort เพื่อนช่วยจัดไฟล์ที่คุณตามหา!?</p><p class="chakra-text css-8uhtka">Surapot Sangasap</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/70-breast-cancer-ultrasound-image-segmentation-using-u"><div class="css-9vp29i"><img alt="Breast Cancer Ultrasound Image Segmentation Using U-Net" src="/showcase/images/2023/70/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Breast Cancer Ultrasound Image Segmentation Using U-Net</p><p class="chakra-text css-8uhtka">Suweeraya Noensai</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/71-check-student-attendance-by-face-detection"><div class="css-9vp29i"><img alt="Check student attendance by face detection" src="/showcase/images/2023/71/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Check student attendance by face detection</p><p class="chakra-text css-8uhtka">Atibodee Kuiprasert</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/72-avocado-ripeness-predictor"><div class="css-9vp29i"><img alt="Avocado Ripeness Predictor" src="/showcase/images/2023/72/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Avocado Ripeness Predictor</p><p class="chakra-text css-8uhtka">Alongkorn Kaewprom</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/73-mediapipe"><div class="css-9vp29i"><img alt="โมเดลการแปลภาษามือไทยด้วย MediaPipe" src="/showcase/images/2023/73/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">โมเดลการแปลภาษามือไทยด้วย MediaPipe</p><p class="chakra-text css-8uhtka">Arucha Khematharonon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/75-cloud-classy"><div class="css-9vp29i"><img alt="Cloud Classy ระบบแยกประเภทของเมฆ" src="/showcase/images/2023/75/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Cloud Classy ระบบแยกประเภทของเมฆ</p><p class="chakra-text css-8uhtka">Thanutham Supphaphon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/77-bulletbrief-make-videos-brief-with-bullet-points"><div class="css-9vp29i"><img alt="BulletBrief — Make videos brief with bullet points" src="/showcase/images/2023/77/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">BulletBrief — Make videos brief with bullet points</p><p class="chakra-text css-8uhtka">Darakarn Limkool</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/78-sitting-posture-estimate"><div class="css-9vp29i"><img alt="Sitting Posture Estimate" src="/showcase/images/2023/78/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Sitting Posture Estimate</p><p class="chakra-text css-8uhtka">Aritat Suriyapattanapong</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/79-how-to-know-percent-your-sound?"><div class="css-9vp29i"><img alt="How to know percent your sound?" src="/showcase/images/2023/79/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">How to know percent your sound?</p><p class="chakra-text css-8uhtka">Pittinan Wettayanon</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/80-diabetic-foot-ulcers-classification-by-using-planter-foot-thermogram-with-vision-transformer"><div class="css-9vp29i"><img alt="Diabetic Foot Ulcers Classification by using planter foot Thermogram with Vision Transformer (ViT)" src="/showcase/images/2023/80/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Diabetic Foot Ulcers Classification by using planter foot Thermogram with Vision Transformer (ViT)</p><p class="chakra-text css-8uhtka">Picha Jetsadapattarakul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/81-pseudobulbar-palsy-detection-with-wav2vec2-and-openai-whisper"><div class="css-9vp29i"><img alt="Pseudobulbar Palsy Detection with Wav2Vec2 and OpenAI Whisper" src="/showcase/images/2023/81/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Pseudobulbar Palsy Detection with Wav2Vec2 and OpenAI Whisper</p><p class="chakra-text css-8uhtka">Jirat Chiaranaipanich/มัธยมศึกษาปีที่ 4.0</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/82-manga-recommendation"><div class="css-9vp29i"><img alt="Manga Recommendation" src="/showcase/images/2023/82/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Manga Recommendation</p><p class="chakra-text css-8uhtka">Jenta Wonglertsakul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/83-woodsight"><div class="css-9vp29i"><img alt="WoodSight" src="/showcase/images/2023/83/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">WoodSight</p><p class="chakra-text css-8uhtka">Chetphisuth Tongpa</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/84-mini-ai-doctor"><div class="css-9vp29i"><img alt="Mini AI Doctor: Disease Prediction" src="/showcase/images/2023/84/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Mini AI Doctor: Disease Prediction</p><p class="chakra-text css-8uhtka">Kornrawee Kochtat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/85-conversation-generation"><div class="css-9vp29i"><img alt="conversation generation" src="/showcase/images/2023/85/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">conversation generation</p><p class="chakra-text css-8uhtka">Krittiwit Kampradam</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/87-artipost-the-poster-generator-ai"><div class="css-9vp29i"><img alt="ArtiPost: The Poster Generator AI" src="/showcase/images/2023/87/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">ArtiPost: The Poster Generator AI</p><p class="chakra-text css-8uhtka">Pannatat Pipopkullaporn</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/89-pm2.5-time-series-forecasting"><div class="css-9vp29i"><img alt="PM2.5 Time Series Forecasting" src="/showcase/images/2023/89/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">PM2.5 Time Series Forecasting</p><p class="chakra-text css-8uhtka">Natthawee Naewkumpol</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/91-t2e-vocabulary-exam-generator"><div class="css-9vp29i"><img alt="T2E Vocabulary Exam Generator" src="/showcase/images/2023/91/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">T2E Vocabulary Exam Generator</p><p class="chakra-text css-8uhtka">Nutnornont Chamadol</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/92-ai-checker"><div class="css-9vp29i"><img alt="AI หมากฮอสสากล" src="/showcase/images/2023/92/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AI หมากฮอสสากล</p><p class="chakra-text css-8uhtka">Nutdanai Jaratwiboonkul</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/93-dog-breed-classification"><div class="css-9vp29i"><img alt="Dog Breed Classification" src="/showcase/images/2023/93/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Dog Breed Classification</p><p class="chakra-text css-8uhtka">Pakin Olanraktham</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/94-text2tags"><div class="css-9vp29i"><img alt="Text2Tags" src="/showcase/images/2023/94/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Text2Tags</p><p class="chakra-text css-8uhtka">Pantai Suyasri</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/95-teeor"><div class="css-9vp29i"><img alt="TEEOR" src="/showcase/images/2023/95/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TEEOR</p><p class="chakra-text css-8uhtka">Pataradanai Akkratch</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/96-catsification"><div class="css-9vp29i"><img alt="CATsification" src="/showcase/images/2023/96/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">CATsification</p><p class="chakra-text css-8uhtka">Pawinthawat Chandravat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/97-ai-fallingasleepdriving"><div class="css-9vp29i"><img alt="AI FallingAsleepDriving (AI ตรวจสอบผู้ขับขี่หลับใน)" src="/showcase/images/2023/97/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AI FallingAsleepDriving (AI ตรวจสอบผู้ขับขี่หลับใน)</p><p class="chakra-text css-8uhtka">Puratsakorn Kietnonthapat</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/98-virtual-coding-mentor"><div class="css-9vp29i"><img alt="Virtual Coding Mentor" src="/showcase/images/2023/98/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Virtual Coding Mentor</p><p class="chakra-text css-8uhtka">Pipatpong Chuchuai</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2023/99-phish-off"><div class="css-9vp29i"><img alt="Phish-Off" src="/showcase/images/2023/99/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Phish-Off</p><p class="chakra-text css-8uhtka">Plengpin Tongdon-Ngao</p></div></div></a></div></div></div><div tabindex="0" aria-labelledby="tabs-1--tab-2" role="tabpanel" hidden="" id="tabs-1--tabpanel-2" class="chakra-tabs__tab-panel css-a5mhaz"><div class="css-bcb7hj"><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/A-Lip-Reader"><div class="css-9vp29i"><img alt="A Lip Reader" src="/showcase/images/2022/53/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">A Lip Reader</p><p class="chakra-text css-8uhtka">พุทธคุณ บุญชัย (ข้าวตู)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/AI-%E0%B9%81%E0%B8%A2%E0%B8%81%E0%B9%81%E0%B8%A2%E0%B8%B0%E0%B9%81%E0%B8%A1%E0%B8%87%E0%B8%94%E0%B8%B2%E0%B8%88%E0%B8%B2%E0%B8%99-%E0%B8%81%E0%B8%B1%E0%B8%9A-%E0%B9%81%E0%B8%A1%E0%B8%87%E0%B8%94%E0%B8%B2%E0%B8%96%E0%B9%89%E0%B8%A7%E0%B8%A2"><div class="css-9vp29i"><img alt="AI แยกแยะแมงดาจาน กับ แมงดาถ้วย" src="/showcase/images/2022/39/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">AI แยกแยะแมงดาจาน กับ แมงดาถ้วย</p><p class="chakra-text css-8uhtka">ภัคพล อาจบุราย (หลุยส์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/American-Sign-Language"><div class="css-9vp29i"><img alt="American Sign Language" src="/showcase/images/2022/52/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">American Sign Language</p><p class="chakra-text css-8uhtka">กรกมล แสงสว่าง (เบลล์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Auto-Lyric-Recognizer"><div class="css-9vp29i"><img alt="Auto Lyric Recognizer" src="/showcase/images/2022/28/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Auto Lyric Recognizer</p><p class="chakra-text css-8uhtka">กิตติพงศ์ เทพอยู่ (ปืน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Automatic-E2E-Thai-Question-Generation-with-MT5"><div class="css-9vp29i"><img alt="Automatic E2E Thai Question Generation with MT5" src="/showcase/images/2022/62/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Automatic E2E Thai Question Generation with MT5</p><p class="chakra-text css-8uhtka">ปรินทพัฒน์ เพ็งพันธุ์ (ปริน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/BACK-(Blind-All-Can-Know)---Action-Captioning-for-Blinds"><div class="css-9vp29i"><img alt="BACK (Blind All Can Know) - Action Captioning for Blinds" src="/showcase/images/2022/21/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">BACK (Blind All Can Know) - Action Captioning for Blinds</p><p class="chakra-text css-8uhtka">โชติวัฒน์ ตั้งสถาพร (ไนน์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Brain-Tumor-Segmentation-using-SegResNet"><div class="css-9vp29i"><img alt="Brain Tumor Segmentation using SegResNet" src="/showcase/images/2022/43/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Brain Tumor Segmentation using SegResNet</p><p class="chakra-text css-8uhtka">ณัฐวดี ลีภัทรกิจ (กิ่งแก้ว)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Cactus-Classification-with-Fastai"><div class="css-9vp29i"><img alt="Cactus Classification with Fastai" src="/showcase/images/2022/24/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Cactus Classification with Fastai</p><p class="chakra-text css-8uhtka">ปัณณธร กรุดทอง (โฟกัส)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Chaos-EDM-Generating-EDM-Song-with-VAE-(Variational-Autoencoder)-Spectrogram"><div class="css-9vp29i"><img alt="Chaos EDM: Generating EDM Song with VAE (Variational Autoencoder) Spectrogram" src="/showcase/images/2022/34/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Chaos EDM: Generating EDM Song with VAE (Variational Autoencoder) Spectrogram</p><p class="chakra-text css-8uhtka">ณยศ สุวัฒโน (ไมค์กี้)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Classical-Music-Generator"><div class="css-9vp29i"><img alt="Classical Music Generator" src="/showcase/images/2022/44/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Classical Music Generator</p><p class="chakra-text css-8uhtka">มณิสรา แซ่จัน (ฟิล์ม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Crossec--%E0%B8%A3%E0%B8%B0%E0%B8%9A%E0%B8%9A%E0%B8%AA%E0%B9%88%E0%B8%87%E0%B9%80%E0%B8%AA%E0%B8%A3%E0%B8%B4%E0%B8%A1%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%97%E0%B8%B3%E0%B8%9B%E0%B8%8F%E0%B8%B4%E0%B8%9A%E0%B8%B1%E0%B8%95%E0%B8%B4%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B9%80%E0%B8%99%E0%B8%B7%E0%B9%89%E0%B8%AD%E0%B9%80%E0%B8%A2%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B8%9E%E0%B8%B7%E0%B8%8A%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2%E0%B8%9B%E0%B8%B1%E0%B8%8D%E0%B8%8D%E0%B8%B2%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B8%94%E0%B8%B4%E0%B8%A9%E0%B8%90%E0%B9%8C"><div class="css-9vp29i"><img alt="Crossec : ระบบส่งเสริมการทำปฏิบัติการเนื้อเยื่อพืชด้วยปัญญาประดิษฐ์" src="/showcase/images/2022/51/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Crossec : ระบบส่งเสริมการทำปฏิบัติการเนื้อเยื่อพืชด้วยปัญญาประดิษฐ์</p><p class="chakra-text css-8uhtka">วิทวัส กิติภัทร์ถาวร (เอิร์ธ)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Debunker-ML-%E0%B8%95%E0%B8%A3%E0%B8%A7%E0%B8%88%E0%B8%88%E0%B8%B1%E0%B8%9A%E0%B8%82%E0%B9%88%E0%B8%B2%E0%B8%A7%E0%B8%A5%E0%B8%A7%E0%B8%87"><div class="css-9vp29i"><img alt="Debunker: ML ตรวจจับข่าวลวง" src="/showcase/images/2022/42/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Debunker: ML ตรวจจับข่าวลวง</p><p class="chakra-text css-8uhtka">นิธิวัฒน์ สิริรัตนชัยกุล (ตง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Detect-and-collect-COVID-19-data-more-faster-by-using-ATK-OCR-Classification-(AOC)-model"><div class="css-9vp29i"><img alt="Detect and collect COVID-19 data more faster by using ATK-OCR Classification (AOC) model" src="/showcase/images/2022/55/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Detect and collect COVID-19 data more faster by using ATK-OCR Classification (AOC) model</p><p class="chakra-text css-8uhtka">ธนอนันท์ เฉลิมพันธ์ (เอ็ม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Edge-to-Face-Drawing-Realistic-Faces-from-Canny-Edges"><div class="css-9vp29i"><img alt="Edge-to-Face: Drawing Realistic Faces from Canny Edges" src="/showcase/images/2022/26/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Edge-to-Face: Drawing Realistic Faces from Canny Edges</p><p class="chakra-text css-8uhtka">นิธิศรัฎฐ์ พุฒิภาพงศ์ (พลัส)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Emotion-Detection-from-Facial-Micro-experessions"><div class="css-9vp29i"><img alt="Emotion Detection from Facial Micro-experessions" src="/showcase/images/2022/61/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Emotion Detection from Facial Micro-experessions</p><p class="chakra-text css-8uhtka">ครองภพ มั่นคง (ไบรท์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Fake-Product-Detection-on-Online-Retail"><div class="css-9vp29i"><img alt="Fake Product Detection on Online Retail" src="/showcase/images/2022/23/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Fake Product Detection on Online Retail</p><p class="chakra-text css-8uhtka">เจษฎา ปราณี (แจ็ค)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Find-Water-from-Satellite-Images-Using-U-Net-Image-Segmentation-with-Pytorch"><div class="css-9vp29i"><img alt="Find Water from Satellite Images Using U-Net Image Segmentation with Pytorch" src="/showcase/images/2022/60/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Find Water from Satellite Images Using U-Net Image Segmentation with Pytorch</p><p class="chakra-text css-8uhtka">วรกาญจน์ ลาสุดี (ปีใหม่)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Food-Ingredients-Label-Reader-for-Food-Allergy"><div class="css-9vp29i"><img alt="Food Ingredients Label Reader for Food Allergy" src="/showcase/images/2022/25/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Food Ingredients Label Reader for Food Allergy</p><p class="chakra-text css-8uhtka">พีรณัฐ เมฆวิศิษฏ์ (ปอนด์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Game-Recommendation-by-using-Neural-Network-Embeddings"><div class="css-9vp29i"><img alt="Game Recommendation by using Neural Network Embeddings" src="/showcase/images/2022/33/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Game Recommendation by using Neural Network Embeddings</p><p class="chakra-text css-8uhtka">มาวิน ศรีชาติ (วิน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/GANime-FullBody-%E0%B8%A7%E0%B8%B2%E0%B8%94%E0%B8%A3%E0%B8%B9%E0%B8%9B%E0%B8%95%E0%B8%B1%E0%B8%A7%E0%B8%A5%E0%B8%B0%E0%B8%84%E0%B8%A3%E0%B8%AD%E0%B8%99%E0%B8%B4%E0%B9%80%E0%B8%A1%E0%B8%B0(%E0%B8%AA%E0%B8%B2%E0%B8%A7%E0%B9%86)%E0%B9%81%E0%B8%9A%E0%B8%9A%E0%B9%80%E0%B8%95%E0%B9%87%E0%B8%A1%E0%B8%95%E0%B8%B1%E0%B8%A7-%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-Deep-Learning"><div class="css-9vp29i"><img alt="GANime-FullBody วาดรูปตัวละครอนิเมะ(สาวๆ)แบบเต็มตัว ด้วย Deep Learning" src="/showcase/images/2022/59/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">GANime-FullBody วาดรูปตัวละครอนิเมะ(สาวๆ)แบบเต็มตัว ด้วย Deep Learning</p><p class="chakra-text css-8uhtka">หิรัญกุล พิมพ์ศิริ (ไกด์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Garbage-Detection-with-Tensorflow-Lite"><div class="css-9vp29i"><img alt="Garbage Detection with Tensorflow Lite" src="/showcase/images/2022/36/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Garbage Detection with Tensorflow Lite</p><p class="chakra-text css-8uhtka">กันต์พัจน์ วิเศษสุข (กัน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Image-Transfer-Day-to-Night-and-Night-to-Day"><div class="css-9vp29i"><img alt="Image Transfer Day-to-Night and Night-to-Day" src="/showcase/images/2022/29/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Image Transfer Day-to-Night and Night-to-Day</p><p class="chakra-text css-8uhtka">ณฐกร คเชนทร (เท็น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Is-that-a-Supra"><div class="css-9vp29i"><img alt="Is that a Supra?!" src="/showcase/images/2022/40/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Is that a Supra?!</p><p class="chakra-text css-8uhtka">จิตรบุณย์ ทรัพย์สินทวีลาภ (กั๊ต)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Lamiaceae-Classification-%E0%B9%81%E0%B8%A2%E0%B8%81%E0%B8%9E%E0%B8%B7%E0%B8%8A%E0%B8%A7%E0%B8%87%E0%B8%A8%E0%B9%8C%E0%B8%81%E0%B8%B0%E0%B9%80%E0%B8%9E%E0%B8%A3%E0%B8%B2-3-%E0%B8%8A%E0%B8%99%E0%B8%B4%E0%B8%94"><div class="css-9vp29i"><img alt="Lamiaceae Classification แยกพืชวงศ์กะเพรา 3 ชนิด" src="/showcase/images/2022/45/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Lamiaceae Classification แยกพืชวงศ์กะเพรา 3 ชนิด</p><p class="chakra-text css-8uhtka">วชิรวิทย์ ไชยมาตย์ (เจ้านาย)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Learn-Chinese-Faster-by-Using-Handwritten-Chinese-Character-Recognition-(HCCR)"><div class="css-9vp29i"><img alt="Learn Chinese Faster by Using Handwritten Chinese Character Recognition (HCCR)" src="/showcase/images/2022/50/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Learn Chinese Faster by Using Handwritten Chinese Character Recognition (HCCR)</p><p class="chakra-text css-8uhtka">ภควุฒิ ธรรมาวุฒิกุล (Army)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Microplastic-detection-and-collect-statistical-tebular-data."><div class="css-9vp29i"><img alt="Microplastic detection and collect statistical tebular data." src="/showcase/images/2022/41/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Microplastic detection and collect statistical tebular data.</p><p class="chakra-text css-8uhtka">ภานุวัฒน์ วงศ์พัฒนวุฒิ (ก้อง)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Music-Recognition"><div class="css-9vp29i"><img alt="Music Recognition" src="/showcase/images/2022/30/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Music Recognition</p><p class="chakra-text css-8uhtka">นนทพรรษ วงษ์กัณหา (นน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/My-Little-HR-%E0%B9%82%E0%B8%A1%E0%B9%80%E0%B8%94%E0%B8%A5%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B9%80%E0%B8%A1%E0%B8%B4%E0%B8%99%E0%B9%80%E0%B8%87%E0%B8%B4%E0%B8%99%E0%B9%80%E0%B8%94%E0%B8%B7%E0%B8%AD%E0%B8%99%E0%B8%AD%E0%B8%B2%E0%B8%8A%E0%B8%B5%E0%B8%9E%E0%B8%AA%E0%B8%B2%E0%B8%A2-IT-%E0%B9%83%E0%B8%99%E0%B8%9B%E0%B8%A3%E0%B8%B0%E0%B9%80%E0%B8%97%E0%B8%A8%E0%B9%84%E0%B8%97%E0%B8%A2"><div class="css-9vp29i"><img alt="My Little HR: โมเดลประเมินเงินเดือนอาชีพสาย IT ในประเทศไทย" src="/showcase/images/2022/58/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">My Little HR: โมเดลประเมินเงินเดือนอาชีพสาย IT ในประเทศไทย</p><p class="chakra-text css-8uhtka">กันตพงศ์ วงศ์พานิชย์ (เติร์ด)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/NLP-for-genre-predictions-on-FFnet-an-antithesis-to-utilitarianism"><div class="css-9vp29i"><img alt="NLP for genre predictions on FFnet: an antithesis to utilitarianism" src="/showcase/images/2022/38/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">NLP for genre predictions on FFnet: an antithesis to utilitarianism</p><p class="chakra-text css-8uhtka">zeiosis@</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Object-Detection-in-White-Blood-Cells-for-Leukemia"><div class="css-9vp29i"><img alt="Object Detection in White Blood Cells for Leukemia" src="/showcase/images/2022/64/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Object Detection in White Blood Cells for Leukemia</p><p class="chakra-text css-8uhtka">แพรวา ชูบ้านนา (แพรว)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Obstacle-Detection-for-Blind-people-%E0%B8%8A%E0%B9%88%E0%B8%A7%E0%B8%A2%E0%B9%80%E0%B8%AB%E0%B8%A5%E0%B8%B7%E0%B8%AD%E0%B8%9C%E0%B8%B9%E0%B9%89%E0%B8%9E%E0%B8%B4%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%97%E0%B8%B2%E0%B8%87%E0%B8%AA%E0%B8%B2%E0%B8%A2%E0%B8%95%E0%B8%B2%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-Deep-Learning"><div class="css-9vp29i"><img alt="Obstacle Detection for Blind people ช่วยเหลือผู้พิการทางสายตาด้วย Deep Learning" src="/showcase/images/2022/54/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Obstacle Detection for Blind people ช่วยเหลือผู้พิการทางสายตาด้วย Deep Learning</p><p class="chakra-text css-8uhtka">เทพบดินทร์ ใจอินสม (ฟู่)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Plant-Disease-Classification"><div class="css-9vp29i"><img alt="Plant Disease Classification" src="/showcase/images/2022/47/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Plant Disease Classification</p><p class="chakra-text css-8uhtka">รัชชานนท์ มุขแก้ว (นนท์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/PsychNLP-A-BERT-based-NLP-model-as-a-screening-tool-to-help-classify-the-risks-of-depression-and-suicide"><div class="css-9vp29i"><img alt="PsychNLP: A BERT-based NLP model as a screening tool to help classify the risks of depression and suicide" src="/showcase/images/2022/57/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">PsychNLP: A BERT-based NLP model as a screening tool to help classify the risks of depression and suicide</p><p class="chakra-text css-8uhtka">พลกฤต สาตสิน (เจ)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/RL-in-Traffic-Management"><div class="css-9vp29i"><img alt="RL in Traffic Management" src="/showcase/images/2022/49/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">RL in Traffic Management</p><p class="chakra-text css-8uhtka">ณดล พิพัฒนติกานันท์ (ไตตั้น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Sick-Pig-Classifier"><div class="css-9vp29i"><img alt="Sick Pig Classifier" src="/showcase/images/2022/37/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Sick Pig Classifier</p><p class="chakra-text css-8uhtka">ภวัต ลีชาแสน (บีม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Single-Note-Music-Classification"><div class="css-9vp29i"><img alt="Single Note Music Classification" src="/showcase/images/2022/65/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Single Note Music Classification</p><p class="chakra-text css-8uhtka">ณภัทร เสรีรักษ์ (นีร)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Text-to-image-synthesis-with-VQGAN-ThCLIP"><div class="css-9vp29i"><img alt="Text-to-image synthesis with VQGAN-ThCLIP" src="/showcase/images/2022/32/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Text-to-image synthesis with VQGAN-ThCLIP</p><p class="chakra-text css-8uhtka">ภูริช ศิริทิพย์ (มาร์ค)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/TextDoe-%E0%B9%82%E0%B8%A1%E0%B9%80%E0%B8%94%E0%B8%A5%E0%B8%88%E0%B8%B3%E0%B9%81%E0%B8%99%E0%B8%81%E0%B9%81%E0%B8%A7%E0%B8%94%E0%B8%A7%E0%B8%87%E0%B8%9A%E0%B8%97%E0%B8%84%E0%B8%A7%E0%B8%B2%E0%B8%A1%E0%B8%AA%E0%B8%B4%E0%B9%88%E0%B8%87%E0%B8%9E%E0%B8%B4%E0%B8%A1%E0%B8%9E%E0%B9%8C"><div class="css-9vp29i"><img alt="TextDoe: โมเดลจำแนกแวดวงบทความสิ่งพิมพ์" src="/showcase/images/2022/27/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TextDoe: โมเดลจำแนกแวดวงบทความสิ่งพิมพ์</p><p class="chakra-text css-8uhtka">โชติอนันต์ทรัพย์ โสภาเคน (โชกุน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/TLDR;-Terms-and-Conditions-Summarizer"><div class="css-9vp29i"><img alt="TLDR; Terms and Conditions Summarizer" src="/showcase/images/2022/48/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">TLDR; Terms and Conditions Summarizer</p><p class="chakra-text css-8uhtka">ศุภโชค บุตรดีขันธ์ (บูม)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Using-Machine-Learning-to-create-Auto-Pitch-Writer-for-UTAU"><div class="css-9vp29i"><img alt="Using Machine Learning to create Auto Pitch Writer for UTAU" src="/showcase/images/2022/63/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Using Machine Learning to create Auto Pitch Writer for UTAU</p><p class="chakra-text css-8uhtka">จิรา กุลจิราพงษ์ (จิรา)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/Violence-Detection"><div class="css-9vp29i"><img alt="Violence Detection" src="/showcase/images/2022/22/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Violence Detection</p><p class="chakra-text css-8uhtka">ชินวัตร นาไชยธง (ม่อน)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/vTranslator-Transcribe-and-Translate-VTuber-using-Wav2Vec2"><div class="css-9vp29i"><img alt="vTranslator: Transcribe and Translate VTuber using Wav2Vec2" src="/showcase/images/2022/31/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">vTranslator: Transcribe and Translate VTuber using Wav2Vec2</p><p class="chakra-text css-8uhtka">ธนภณ ทองจำนงค์ (ธันย์)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/WanchanBERTa-Thai-Grammarly"><div class="css-9vp29i"><img alt="WanchanBERTa Thai Grammarly" src="/showcase/images/2022/35/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">WanchanBERTa Thai Grammarly</p><p class="chakra-text css-8uhtka">อิทธิพัฒน์ ปานขำ (มาร์จิ้น)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/%E0%B9%82%E0%B8%A1%E0%B9%80%E0%B8%94%E0%B8%A5-CNN-%E0%B8%AA%E0%B8%B3%E0%B8%AB%E0%B8%A3%E0%B8%B1%E0%B8%9A%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%88%E0%B8%B3%E0%B9%81%E0%B8%99%E0%B8%81%E0%B8%AA%E0%B8%B1%E0%B8%8D%E0%B8%8D%E0%B8%B2%E0%B8%93%E0%B8%AA%E0%B8%A1%E0%B8%AD%E0%B8%87%E0%B9%83%E0%B8%99%E0%B8%A3%E0%B8%B0%E0%B8%9A%E0%B8%9A-SSVEP-BCI-%E0%B8%AA%E0%B8%B3%E0%B8%AB%E0%B8%A3%E0%B8%B1%E0%B8%9A%E0%B9%84%E0%B8%A1%E0%B9%80%E0%B8%81%E0%B8%A3%E0%B8%99-(A-CNN-for-Classification-Task-in-SSVEP-BCI-for-Migraine)"><div class="css-9vp29i"><img alt="โมเดล CNN สำหรับการจำแนกสัญญาณสมองในระบบ SSVEP-BCI สำหรับไมเกรน (A CNN for Classification Task in SSVEP-BCI for Migraine)" src="/showcase/images/2022/56/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">โมเดล CNN สำหรับการจำแนกสัญญาณสมองในระบบ SSVEP-BCI สำหรับไมเกรน (A CNN for Classification Task in SSVEP-BCI for Migraine)</p><p class="chakra-text css-8uhtka">ฆนัท บุญจง (เค)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2022/%E0%B8%AA%E0%B8%A3%E0%B9%89%E0%B8%B2%E0%B8%87%E0%B8%AA%E0%B8%A3%E0%B8%A3%E0%B8%9A%E0%B8%97%E0%B9%80%E0%B8%9E%E0%B8%A5%E0%B8%87-Undertale-%E0%B8%9C%E0%B9%88%E0%B8%B2%E0%B8%99-LSTM-%E0%B9%81%E0%B8%A5%E0%B8%B0-Teacher-Forcing-RNN"><div class="css-9vp29i"><img alt="สร้างสรรบทเพลง Undertale ผ่าน LSTM และ Teacher Forcing RNN" src="/showcase/images/2022/46/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">สร้างสรรบทเพลง Undertale ผ่าน LSTM และ Teacher Forcing RNN</p><p class="chakra-text css-8uhtka">นพวิทย์ ตันติศิริวัฒน์ (ภีม)</p></div></div></a></div></div></div><div tabindex="0" aria-labelledby="tabs-1--tab-3" role="tabpanel" hidden="" id="tabs-1--tabpanel-3" class="chakra-tabs__tab-panel css-a5mhaz"><div class="css-bcb7hj"><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/001-foody-dudy"><div class="css-9vp29i"><img alt="FoodyDudy" src="/showcase/images/2021/001/1.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">FoodyDudy</p><p class="chakra-text css-8uhtka">Phacharaphol Somboontham (Gemmy)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/002-LiDAR-3D-Point-Cloud-Object-Detection-for-Autonomous-Vehicle"><div class="css-9vp29i"><img alt="LiDAR 3D Point Cloud Object Detection for Autonomous Vehicle" src="/showcase/images/2021/002/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">LiDAR 3D Point Cloud Object Detection for Autonomous Vehicle</p><p class="chakra-text css-8uhtka">Thanapat Chotipun (Patrick)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/003-Lalita-Chinese-Thai-Machine-Translation"><div class="css-9vp29i"><img alt="Lalita Chinese-Thai Machine Translation " src="/showcase/images/2021/003/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Lalita Chinese-Thai Machine Translation </p><p class="chakra-text css-8uhtka">Lalita Deelert (Looktarn)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/004-%E0%B9%81%E0%B8%99%E0%B8%B0%E0%B8%99%E0%B8%B3%E0%B8%A3%E0%B8%B2%E0%B8%84%E0%B8%B2%E0%B8%A3%E0%B8%B9%E0%B8%9B%E0%B8%84%E0%B8%AD%E0%B8%A1%E0%B8%A1%E0%B8%B4%E0%B8%8A%E0%B8%8A%E0%B8%B1%E0%B8%99%E0%B8%AD%E0%B8%99%E0%B8%B4%E0%B9%80%E0%B8%A1%E0%B8%B0%E0%B8%94%E0%B9%89%E0%B8%A7%E0%B8%A2-machine-learning-%E0%B9%82%E0%B8%94%E0%B8%A2-fastai"><div class="css-9vp29i"><img alt="แนะนำราคารูปคอมมิชชันอนิเมะด้วย machine learning โดย fastai" src="/showcase/images/2021/004/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">แนะนำราคารูปคอมมิชชันอนิเมะด้วย machine learning โดย fastai</p><p class="chakra-text css-8uhtka">Prad Rattanakijsoonthorn (BB)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/005-Thai-Text-to-Speech-with-Tacotron"><div class="css-9vp29i"><img alt="Thai Text-to-Speech with Tacotron" src="/showcase/images/2021/005/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Thai Text-to-Speech with Tacotron</p><p class="chakra-text css-8uhtka">Rajasurang Wongkrasaemongkol (Prim)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/006-Salmon-Classifier-%E0%B9%80%E0%B8%A3%E0%B8%B7%E0%B9%88%E0%B8%AD%E0%B8%87%E0%B8%A7%E0%B8%B8%E0%B9%88%E0%B8%99%E0%B9%86%E0%B8%82%E0%B8%AD%E0%B8%87%E0%B8%9B%E0%B8%A5%E0%B8%B2%E0%B9%81%E0%B8%8B%E0%B8%A5%E0%B8%A1%E0%B8%AD%E0%B8%99"><div class="css-9vp29i"><img alt="Salmon Classifier: เรื่องวุ่นๆของปลาแซลมอน" src="/showcase/images/2021/006/01.png" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Salmon Classifier: เรื่องวุ่นๆของปลาแซลมอน</p><p class="chakra-text css-8uhtka">Tanakrit Saiphan (Mookrob)</p></div></div></a></div><div class="css-reijdp"><a class="chakra-link css-10qsrqw" href="/showcase/2021/007-Thai-Music-Generation-with-VAE"><div class="css-9vp29i"><img alt="Thai Music (Ranat Ek) Generation with Variational Autoencoder" src="/showcase/images/2021/007/01.jpg" class="chakra-image css-bh4wo8"/></div><div class="css-1fh9ko"><div class="css-0"><p class="chakra-text css-8uhtka">Thai Music 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