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Titlebook: Secure Knowledge Management In The Artificial Intelligence Era; 9th International Co Ram Krishnan,H. Raghav Rao,Ziming Zhao Conference proc

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發(fā)表于 2025-3-21 19:05:02 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Secure Knowledge Management In The Artificial Intelligence Era
副標(biāo)題9th International Co
編輯Ram Krishnan,H. Raghav Rao,Ziming Zhao
視頻videohttp://file.papertrans.cn/864/863311/863311.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Secure Knowledge Management In The Artificial Intelligence Era; 9th International Co Ram Krishnan,H. Raghav Rao,Ziming Zhao Conference proc
描述This book constitutes the refereed proceedings of the 9th International Conference On Secure Knowledge Management In Artificial Intelligence Era, SKM 2021, held in San Antonio, TX, USA, in 2021. Due to the COVID-19 pandemic the conference was held online.?.The 11 papers presented were carefully reviewed and selected from 30 submissions. They were organized according to the following topical sections: ?intrusion and malware detection; secure knowledge management; deep learning for security; web and social network.
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; communication channels (information theory); communication systems; computer c
版次1
doihttps://doi.org/10.1007/978-3-030-97532-6
isbn_softcover978-3-030-97531-9
isbn_ebook978-3-030-97532-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Switzerland AG 2022
The information of publication is updating

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Secure Knowledge Management In The Artificial Intelligence Era978-3-030-97532-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Communications in Computer and Information Sciencehttp://image.papertrans.cn/s/image/863311.jpg
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Analyzing CNN Models’ Sensitivity to?the?Ordering of?Non-natural Datarformance is not well-studied. In this paper, we investigate this problem by examining several different CNN models. We define a functional algorithm for ordering, show that order importance in CNNs is model dependent and that depending on the model, statistical relationships are an important tool in establishing order with better performance.
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Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Reviewcoordinated manner to perpetuate sophisticated attacks that could bring down the entire network and many critical hosts in the network. Increasingly advanced deep and machine learning-based solutions have been used in threat detection and protection. The application of these techniques has been revi
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