The self supervised multimodal semantic transmission mechanism for complex network environments

With the rapid development of intelligent transportation systems, the challenge of achieving efficient and accurate multimodal traffic data transmission and collaborative processing in complex network environments with bandwidth limitations, signal interference, and high concurrency has become a key...

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Vydáno v:	Scientific reports Ročník 15; číslo 1; s. 29899 - 21
Hlavní autoři:	Zou, Jiajun, Wan, Zhiping, Wang, Feng, Ye, Shitong, Liu, Shaojiang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 14.08.2025 Nature Publishing Group Nature Portfolio
Témata:	631/477 639/166 639/705 Algorithms Bandwidths Collaboration Communication Data transmission Efficiency Graph neural network Humanities and Social Sciences Intelligent transportation Latency Learning Lidar multidisciplinary Multimodal semantic communication Neural networks Optimization Reinforcement Reinforcement learning Resource management Science Science (multidisciplinary) Self-supervised learning Semantics Spectrum allocation Traffic accidents & safety Traffic control Traffic flow Vehicles Intelligent transportation Multimodal semantic communication Graph neural network Self-supervised learning Reinforcement learning
ISSN:	2045-2322, 2045-2322
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