4 citations · 10 across the 3 of their papers we have counts for
3 papers
eess.SP2023★ 3 cited
SwinJSCC: Taming Swin Transformer for Deep Joint Source-Channel Coding
Ke Yang, Sixian Wang, Jincheng Dai +3
As one of the key techniques to realize semantic communications, end-to-end optimized neural joint source-channel coding (JSCC) has made great progress over the past few years. A g…
cs.CV2022★ 4 cited
WITT: A Wireless Image Transmission Transformer for Semantic Communications
Ke Yang, Sixian Wang, Jincheng Dai +3
In this paper, we aim to redesign the vision Transformer (ViT) as a new backbone to realize semantic image transmission, termed wireless image transmission transformer (WITT). Prev…
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…