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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Chuanlei Zhang,Jiayang Guo Conference proc

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發(fā)表于 2025-3-21 19:32:48 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advanced Intelligent Computing Technology and Applications
期刊簡稱20th International C
影響因子2023De-Shuang Huang,Chuanlei Zhang,Jiayang Guo
視頻videohttp://file.papertrans.cn/168/167149/167149.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Chuanlei Zhang,Jiayang Guo Conference proc
影響因子.This 13-volume set LNCS 14862-14874 constitutes - in conjunction with the 6-volume set LNAI 14875-14880 and the two-volume set LNBI 14881-14882 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024...The total of 863 regular papers were carefully reviewed and selected from 2189 submissions...This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology...?.
Pindex Conference proceedings 2024
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書目名稱Advanced Intelligent Computing Technology and Applications影響因子(影響力)




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Lineare Netze im Eingeschwungenen Zustand,evaluate our system, we collect MAC layer traffic data over 125 h from more than 40 apps. The experimental results show that MACPrint can achieve an accuracy of over 96% for recognizing apps and actions in the closed-world setting, and obtains an accuracy of over 86% in the open-world setting.
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,Der Stromkreis im Quasistation?ren Zustand,at share the same feature space with IQ samples. Then, the distinct advantages of an IQ fingerprinting model in feature extraction are transferred to its CSI counterpart via an auxiliary training strategy. Finally, the trained CSI fingerprinting model is used to decide which device the sample under
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https://doi.org/10.1007/978-3-662-66188-8d our own practical assembly dataset. What’s more, the practical implementation of a dish-washing machine assembly line shows that our method can help promote both product quality and production efficiency. Our Industrial Assembly Dataset (IndAD) with the video data collected from several practical
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