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Titlebook: Application of Intelligent Systems in Multi-modal Information Analytics; Proceedings of the 2 Vijayan Sugumaran,Zheng Xu,Huiyu Zhou Confere

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發(fā)表于 2025-3-21 16:12:17 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Application of Intelligent Systems in Multi-modal Information Analytics
期刊簡(jiǎn)稱Proceedings of the 2
影響因子2023Vijayan Sugumaran,Zheng Xu,Huiyu Zhou
視頻videohttp://file.papertrans.cn/160/159135/159135.mp4
發(fā)行地址Presents recent research on intelligent systems in multi-modal information analytics.Includes selected papers presented at the 2020 International Conference on Multi-modal Information Analytics (MMIA
學(xué)科分類Advances in Intelligent Systems and Computing
圖書(shū)封面Titlebook: Application of Intelligent Systems in Multi-modal Information Analytics; Proceedings of the 2 Vijayan Sugumaran,Zheng Xu,Huiyu Zhou Confere
影響因子.This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18–19, 2020. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. It addresses a number of broad themes, including data mining, multi-modal informatics, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field..
Pindex Conference proceedings 2021
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Application of Intelligent Systems in Multi-modal Information AnalyticsProceedings of the 2
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https://doi.org/10.1007/978-3-642-69262-8tion to the multidimensional nonuniform field space. It has been applied to the interpolation of the transformer frequency response data. The results prove that the method reduces the noise interference to a certain extent, and therefore the points on the frequency response curve of the transformer
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