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Titlebook: Wireless Algorithms, Systems, and Applications; 16th International C Zhe Liu,Fan Wu,Sajal K. Das Conference proceedings 2021 Springer Natur

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发表于 2025-3-21 19:16:46 | 显示全部楼层 |阅读模式
书目名称Wireless Algorithms, Systems, and Applications
副标题16th International C
编辑Zhe Liu,Fan Wu,Sajal K. Das
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Wireless Algorithms, Systems, and Applications; 16th International C Zhe Liu,Fan Wu,Sajal K. Das Conference proceedings 2021 Springer Natur
描述The three-volume set constitutes the proceedings of the 16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021, which was held during June 25-27, 2021, in Nanjing, China.The 103 full and 57 short papers presented in these proceedings were carefully reviewed and selected from 315 submissions. Part III of the set includes the papers of the contributors that took part in the workshops co-located with the conference.The following topics are covered in the volume: network protocols, signal processing, wireless telecommunication systems, routing algorithms, cryptography, local area networks, and others..
出版日期Conference proceedings 2021
关键词artificial intelligence; bandwidth; communication channels (information theory); communication systems;
版次1
doihttps://doi.org/10.1007/978-3-030-86137-7
isbn_softcover978-3-030-86136-0
isbn_ebook978-3-030-86137-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
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978-3-030-86136-0Springer Nature Switzerland AG 2021
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Wireless Algorithms, Systems, and Applications978-3-030-86137-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
发表于 2025-3-22 11:23:09 | 显示全部楼层
Image Encryption for Wireless Sensor Networks with Modified Logistic Map and New Hash Algorithmy identity authentication by constructing a new Hash function. Experiments have proved that the proposed image algorithm can effectively resist typical attacks and increase the reliability of sending information between nodes.
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Multi-step Domain Adaption Image Classification Network via Attention Mechanism and Multi-level Feats proposed in this paper. Specifically, firstly, the attention mechanism is used to combine the source domain and target domain data to generate an intermediate domain. Secondly, several feature alignment strategies are proposed to align the source domain and the target domain from the pixel and global levels.
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