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ADJSCC

adaptive/attention deep joint source channel coding

Install / Use

/learn @alexxu1988/ADJSCC
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Code: Wireless Image Transmission Using Deep Source Channel Coding with Attention Modules

Adaptive/Attention Deep Joint Source Channel Coding Image text

Datasets:

CIFAR-10 is from inner tensorflow.keras.datasets.cifar10.<br> ImageNet is manually made and is too huge to upload.

Warning:

  1. The provided folder of tensorflow_compression is only for macOS. If you want to use tensorflow_compression in other systems, please use pip to install tensorflow_compression and change corresponding codes reling on tensorflow_compression.
  2. If you want to use ImageNet to test bdjscc_imagenet.py and adjscc_imagenet.py, you can use pip to install tensorflow_dataset and download ImageNet. The corrsponding code of loading ImageNet should be modified.

Citation:

J. Xu, B. Ai, W. Chen, A. Yang, P. Sun and M. Rodrigues, "Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 4, pp. 2315-2328, April 2022, doi: 10.1109/TCSVT.2021.3082521.

If you have any question, please feel free to contact me via: xjl-88410@163.com

Related Skills

View on GitHub
GitHub Stars89
CategoryDevelopment
Updated22d ago
Forks12

Languages

Python

Security Score

95/100

Audited on Mar 11, 2026

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