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Disclaimer:

This is a research project and by definition is unstable. Please write to us if you find something not correct or strange. We are sharing the codes under the condition that reproducing full or part of codes must cite the related paper.

Related Paper:

  • Tong S, Yu X, Li R, et al. Alternate Learning based Sparse Semantic Communications for Visual Transmission, in Proc. PIMRC 2023, Toronto, Canada, Sep. 2023.

Dataset:

For dataset, it is available online at https://www.cs.toronto.edu/~kriz/cifar.html

Choose the version "CIFAR-10 python version, 163 MB".

Run the code:

  • Note: The file "CIFAR-10 python version, 163 MB" shall be downloaded online.

The training example:python -u Train.py --quant 1 --EXP_NAME Cifar_quant

The testing example:python -u Test.py --quant 1 --EXP_NAME Cifar_quant

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Alternate Learning based Sparse Semantic Communications for Visual Transmission

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