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Titlebook: Machine Learning for Cyber Security; 4th International Co Yuan Xu,Hongyang Yan,Jin Li Conference proceedings 2023 The Editor(s) (if applica

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發(fā)表于 2025-3-21 17:39:37 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Machine Learning for Cyber Security
副標(biāo)題4th International Co
編輯Yuan Xu,Hongyang Yan,Jin Li
視頻videohttp://file.papertrans.cn/621/620606/620606.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Machine Learning for Cyber Security; 4th International Co Yuan Xu,Hongyang Yan,Jin Li Conference proceedings 2023 The Editor(s) (if applica
描述The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereed.proceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China..The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions..
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligence; communication systems; computer networks; computer science; computer security; c
版次1
doihttps://doi.org/10.1007/978-3-031-20102-8
isbn_softcover978-3-031-20101-1
isbn_ebook978-3-031-20102-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Deep Spatio-Temporal Decision Fusion Network for Facial Expression Recognition,ct the shallow spatial features of peak expression frame, and the channel weights of spatial features is assigned by squeeze-and-excitation module to attain the weighted spatial features. This allows valid spatial features to be purposefully retained to avoid overfitting. Finally, temporal features
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A Robot Foreign Object Inspection Algorithm for Transmission Line Based on Improved YOLOv5,he YOLOv5 lightweight model proposed in this paper reduces the power consumption of the platform and improves the model detection speed and accuracy. It is more conducive to the deployment of the target detection model in the mobile terminal.
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Research on LSTM Based Traffic Flow Prediction Adaptive Beacon Transmission Period and Power Joint d the LSTM network is used to predict the traffic flow. Then, the combined control algorithm of the adaptive beacon transmission period and transmission power is realized through the predicted parameters. Experimental simulation and analysis show that this algorithm can significantly reduce the dist
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e Feen Pate gestanden sind. Ich erkannte, da? der einstige Lückenbü?er bei liebevoller Behandlung zu einem recht wertvollen Glied in der Gesellschaft seiner literarischen Brüder werden k?nnte und bemühte mich, ihn so rasch als m?glich gesellschaftsf?hig zu machen. Auch der Springer-Verlag zeigte in dankenswer978-3-7091-3465-8978-3-7091-3464-1
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