https://github.com/unshun0120/apply-federatedlearning-into-semanticcommunication

Using Federated Learning to train the model in Semantic Communication in pytorch
https://github.com/unshun0120/apply-federatedlearning-into-semanticcommunication

cifar-10 cnn federated-averaging federated-learning pytorch semantic-communication

Last synced: 22 days ago
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Using Federated Learning to train the model in Semantic Communication in pytorch

• Host: GitHub
• URL: https://github.com/unshun0120/apply-federatedlearning-into-semanticcommunication
• Owner: unshun0120
• Created: 2025-01-10T05:19:56.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-02-09T13:22:26.000Z (8 months ago)
• Last Synced: 2025-02-27T23:39:17.861Z (7 months ago)
• Topics: cifar-10, cnn, federated-averaging, federated-learning, pytorch, semantic-communication
• Language: Python
• Homepage:
• Size: 145 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

          
我好像做出來了哈哈 但準確率很低 差低   

![nlnlXD](https://github.com/user-attachments/assets/b68fdf94-ec6e-45d9-907a-4dbd7b70023f)  

**Apply Federated Learning into Semantic Communication**

---

this project is based on :  

*Federated Learning*  

+ https://github.com/AshwinRJ/Federated-Learning-PyTorch

  

*Semantic Communication*  

+ https://github.com/Azul-9/DeepLearningEnabledSemanticCommunicationSystems   

+ https://github.com/wyzhang-ustb/Predictive-and-Adaptive-Deep-Coding-for-Wireless-Image-Transmission-in-Semantic-Communication   

---

## Before Running  

1. Create a new folder called **"Dataset"** outside the downloaded folder

2. Create a new folder called **"logs"** outside the downloaded folder

3. Create a new folder called **"save"** outside the downloaded folder

4. Create a new folder called **"objects"** inside the **"save"** folder  

  

---

Run  

```

python main.py --gpu=0

```