Lightweight and Adaptive Deep Coding for Wireless Image Transmission in Semantic Communication

Currently, deep learning-based joint source channel coding (JSCC) methods have achieved significant progress in enabling semantic communication. However, existing methods of this type often fall short of meeting the new demands in terms of model parameter size and storage efficiency. To address thes...

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Vydáno v:	IEEE access Ročník 13; s. 158285 - 158301
Hlavní autoři:	Sun, Youming, Wang, Jiafeng, Wei, Lile, Chen, Haiqiang, Dang, Shuping, Li, Xiangcheng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptation models Bandwidth Bandwidths Coding Communication ConvNeXt Decoding Feature extraction Image coding Image communication Image reconstruction Image resolution Image transmission joint source channel coding lightweight model Parameters Semantic communication Semantics Signal to noise ratio Wireless communication wireless image transmission
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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