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Titlebook: Computer Applications; 38th CCF Conference Min Zhang,Bin Xu,Zeguang Lu Conference proceedings 2024 The Editor(s) (if applicable) and The A

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發(fā)表于 2025-3-21 18:36:15 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computer Applications
副標題38th CCF Conference
編輯Min Zhang,Bin Xu,Zeguang Lu
視頻videohttp://file.papertrans.cn/234/233475/233475.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Computer Applications; 38th CCF Conference  Min Zhang,Bin Xu,Zeguang Lu Conference proceedings 2024 The Editor(s) (if applicable) and The A
描述The two-volume set CCIS 1959 and 1960 constitutes the refereed post-conference?proceedings of the 38th CCF National Conference?on?Computer Applications, CCF NCCA 2023, held in Suzhou, China, during July 16–20, 2023..The 39 revised full papers presented in these proceedings were carefully reviewed and selected from 197 submissions. The papers are organized in the following topical sections:.Volume I:.Artificial intelligence and application..Volume II:.Data science and technology; pattern recognition and machine learning;?network communication and security;?frontier and comprehensive applications..
出版日期Conference proceedings 2024
關鍵詞Artificial Intelligence and Applications; Pattern Recognition and Machine Learning; Data Science and T
版次1
doihttps://doi.org/10.1007/978-981-99-8764-1
isbn_softcover978-981-99-8763-4
isbn_ebook978-981-99-8764-1Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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A Review of Intelligent Opponent Modelling Research for Air Combat Simulation Trainingon methods and anti-interference technology of intelligent agents from key technologies such as deep learning and reinforcement learning to provide support for the development of air combat simulation training systems.
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A BMRC Algorithm Based on?Knowledge Enhancement and?Case Regularization for?Aspect Emotion Triplet E this end, this paper proposes a BMRC with knowledge enhancement, which integrates the knowledge of specialized fields into the model, strengthens the connection between specific fields and open fields, increases instance regularization, and pays attention to the contribution of individual instances
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