add examples into architecture

Signed-off-by: Marchons <[email protected]>
kubeedge · Sep 12, 2024 · 17dc163 · 17dc163
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diff --git a/...oposals/algorithms/federated-class-incremental-learning/FCI_SSL_image/architecture_design b/...oposals/algorithms/federated-class-incremental-learning/FCI_SSL_image/architecture_design
diff --git a/...rithms/federated-class-incremental-learning/FCI_SSL_image/federated_learning_architecture b/...rithms/federated-class-incremental-learning/FCI_SSL_image/federated_learning_architecture
diff --git a/...l-learning/Federated Class-Incremental and Semi-Supervised learning Proposal.md b/...l-learning/Federated Class-Incremental and Semi-Supervised learning Proposal.md
@@ -103,7 +103,7 @@ Federated incremental learning is a special kind of federated learning. However
 
 Sedna is a edge-cloud collaborative training AI framework. It support federated learning ability. Base on Sedna, we can have a simple federated learning architecture: 
 
-![image-20240909194418085](FCI_SSL_image/federated_learning_architecture)
+![image-20240912171642528](FCI_SSL_image/federated_learning_architecture)
 
 ##### Implementation Detail
 
@@ -219,7 +219,7 @@ We will leverage the existed *TestEnvManager*, *TestCaseController* and *StoryMa
 
 The overall architecture is shown as follow: 
 
-![image-20240909194437318](FCI_SSL_image/architecture_design)
+![image-20240912172517676](FCI_SSL_image/architecture_design)
 
 ##### Implementation Detail
 
@@ -443,7 +443,7 @@ $$
 
 #### 3.5.1 Federated Learning Example
 
-Base on the architecture above, If user want to implement a federated learning algorithm， they can following the below instruction:
+Base on the architecture above, If user want to implement a federated learning algorithm， ![image-20240912171635194](Federated Class-Incremental and Semi-Supervised learning Proposal.assets/image-20240912171635194.png)they can following the below instruction:
 
 example path: `example/cifar100/federeated_learning/fedavg`