Low-Rank Decomposition for Rate-Adaptive Deep Joint Source-Channel Coding
Author:
Affiliation:
1. Macao Polytechnic University,Faculty of Applied Sciences,Macao SAR,China
2. Macao Polytechnic University,Macao SAR,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10065600/10065601/10065853.pdf?arnumber=10065853
Reference22 articles.
1. Compressing 3DCNNs based on tensor train decomposition
2. Compression of deep convolutional neural networks for fast and low power mobile applications;kim;ArXiv Preprint,2015
3. Deep joint source-channel coding for wire-less image transmission with adaptive rate control;yang;ArXiv Preprint,2021
4. Low Complexity Rate-Adaptive Deep Joint Source Channel Coding for Wireless Image Transmission Using Tensor-Train Decomposition
5. Automated Multi-Stage Compression of Neural Networks
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1. Low Complexity OFDM-Guided DJSCC for Multipath Fading Channels using Tensor Train Decomposition with Fine-Tuning;2023 8th International Conference on Signal and Image Processing (ICSIP);2023-07-08
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