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We present a novel adaptive deep joint source-channel coding (JSCC) scheme for wireless image transmission.
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton, · 2012
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Arash Vosoughi, Pamela C Cosman, and Laurence B Milstein, · 2014
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“Power of deep learning for channel estimation and signal detection in ofdm systems,”
Hao Ye, Geoffrey Ye Li, and Biing-Hwang Juang, · 2017
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“Spatially adaptive computation time for residual networks,”
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“Skipnet: Learning dynamic routing in convolutional networks,”
Xin Wang, Fisher Yu, Zi-Yi Dou, Trevor Darrell, and Joseph E Gonzalez, · 2018
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Xitong Gao, Yiren Zhao, Lukasz Dudziak, Robert Mullins, and Cheng-zhong Xu, · 2018
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“Convolutional networks with adaptive inference graphs,”
Andreas Veit and Serge Belongie, · 2018
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“Blockdrop: Dynamic inference paths in residual networks,”
“Successive refinement of images with deep joint source-channel coding,”
David Burth Kurka and Deniz Gündüz, · 2019
Later among the works it cites.
“Neural joint source-channel coding,”
Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, and Stefano Ermon, · 2019
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“Deepjscc-f: Deep joint source-channel coding of images with feedback,”
David Burth Kurka and Deniz Gündüz, · 2020
Later among the works it cites.
“Super-resolution time-of-arrival estimation using neural networks,”
Yao-Shan Hsiao, Mingyu Yang, and Hun-Seok Kim, · 2021
Closest in time.
“Deep joint source channel coding for wirelessimage transmission with ofdm,”
Mingyu Yang, Chenghong Bian, and Hun-Seok Kim, · 2021
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“Wireless image transmission using deep source channel coding with attention modules,”
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Mingyu Yang, Li-Xuan Chuo, Karan Suri, Lu Liu, Hao Zheng, and Hun-Seok Kim, · 2019
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“Deep joint source-channel coding for wireless image transmission,”
Eirina Bourtsoulatze, David Burth Kurka, and Deniz Gündüz, · 2019
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Jialong Xu, Bo Ai, Wei Chen, Ang Yang, Peng Sun, and Miguel Rodrigues, · 2021
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“Bandwidth-agile image transmission with deep joint source-channel coding,”
David Burth Kurka and Deniz Gündüz, · 2021
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