Google Summer of Code 2021 Additional Projects

Machine Learning with Sea Floor Sampling Video

Project Description:

Traditionally, surverys of the sea floor are conducted via vessel-mounted cameras which record video as the vessel moves in the water. Hundreds of hours of video are recorded and are often manually processed to determine which species are present on the locations in the video. This project seeks to automate the process using image processing. The intern will help prepare machine learning models, such as artificial neural networks, using available video footage from benthic surverying missions. The intern will partner with biology staff and software staff to train the model and perform data validation.

Expected Outcomes: A capable machine learning model which can be used to identify species from video transect data of the sea floor.

Skills required:

Familiarity with a programming language (Python, R) and a general understanding of how machine learning models operate. Experience with image processing is a bonus.

Difficulty:

Moderately difficult

Mentor(s):

Dalton Kell (Software Engineer), Matt Iannucci (Software Engineer), Tara Franey (GIS Specialist), Stephanie Berkman (Biologist), Joe Zottoli (Biologist)

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"Big Gridded Data": Distributed Cloud Storage for Physical Oceanography Data

Project Description:

Storing highly-voluminous and highly-dimensional data has always presented challenges, and while hardware advancements have eased some of the burden, software remains the critical component in data management systems. This project will explore burgeoning solutions in the big-data realm to store massive volumes of highly-dimensional numeric data across distributed cloud platforms. Participants will examine tradeoffs between technologies and develop deeper understanding of how new data storage and access solutions may be implemented in the oceanography industry.

Expected Outcomes:

A software cost-benefit analysis of data storage and access scenarios.

Skills required:

Familiarity with Linux/UNIX operating systems and a working knowledge of Python, C/C++. Understanding basic database architecture is a plus.

Difficulty:

Moderately difficult

Mentor(s):

Dalton Kell (Software Engineer), Ben Adams (Software Engineer)