Semantic Communications for Joint Image Recovery and Classification
Author:
Affiliation:
1. SSE and FNii, The Chinese University of Hong Kong (Shenzhen),Shenzhen,China
2. Shenzhen Research Institute of Big Data,Shenzhen,China
3. Beijing Jiaotong University,State Key Laboratory of Rail Traffic Control and Safety,Beijing,China
Funder
National Natural Science Foundation of China
National Key R&D Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10464388/10464393/10464706.pdf?arnumber=10464706
Reference15 articles.
1. Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications
2. Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G
3. Deep Learning-Enabled Semantic Communication Systems With Task-Unaware Transmitter and Dynamic Data
4. Deep Joint Source-Channel Coding for Wireless Image Transmission
5. Deep Learning Enabled Semantic Communication Systems
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Semantic Communications for Image Recovery and Classification via Deep Joint Source and Channel Coding;IEEE Transactions on Wireless Communications;2024-08
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