5 citations · 12 across the 6 of their papers we have counts for
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cs.IT2022★ 3 cited
Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding
Jincheng Dai, Sixian Wang, Ke Yang +5
The emerging field semantic communication is driving the research of end-to-end data transmission. By utilizing the powerful representation ability of deep learning models, learned…
cs.IT2021
Nonlinear Transform Source-Channel Coding for Semantic Communications
Jincheng Dai, Sixian Wang, Kailin Tan +4
In this paper, we propose a class of high-efficiency deep joint source-channel coding methods that can closely adapt to the source distribution under the nonlinear transform, it ca…
cs.IT2021★ 5 cited
Learning to Decode Protograph LDPC Codes
Jincheng Dai, Kailin Tan, Zhongwei Si +4
The recent development of deep learning methods provides a new approach to optimize the belief propagation (BP) decoding of linear codes. However, the limitation of existing works…