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Titlebook: Image and Video Technology; 10th Pacific-Rim Sym Han Wang,Wei Lin,Haoge Jiang Conference proceedings 2023 Springer Nature Switzerland AG 20

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书目名称Image and Video Technology
副标题10th Pacific-Rim Sym
编辑Han Wang,Wei Lin,Haoge Jiang
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Image and Video Technology; 10th Pacific-Rim Sym Han Wang,Wei Lin,Haoge Jiang Conference proceedings 2023 Springer Nature Switzerland AG 20
描述This book constitutes the conference proceedings of the 10th Pacific Rim Symposium on Image and Video Technology, PSIVT 2022, held in Bintan Island, Indonesia, in November 2022..A total of 15 papers were carefully reviewed and selected from 18 submissions. The main conference focuses on theoretical advances or practical implementations in image and video technology..
出版日期Conference proceedings 2023
关键词Image and Video Technology; NLP; Deep Learning; Machine Learning; Imaging and Graphics Hardware and Visu
版次1
doihttps://doi.org/10.1007/978-3-031-26431-3
isbn_softcover978-3-031-26430-6
isbn_ebook978-3-031-26431-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2023
The information of publication is updating

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Xinyi Gao,Minh Nguyen,Wei Qi Yanelection.  Although they are non-related in male-philopatric society, they usually aggregate in a group, enjoy priority access to food, determine which male is the alpha male, and generally maintain much more p978-981-13-8061-7978-981-13-8059-4Series ISSN 2190-5967 Series E-ISSN 2190-5975
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Minh-Vuong Nguyen-Thi,Huy Le,Truong Le,Tung Le,Huy Tien Nguyen
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A Federated Learning Approach for Text Classification Using NLP,sing the FL approach, more data has to be collected, eliminating data gaps and ensuring data security. The focus of this research is to increase the model’s accuracy by collaborating with FL approaches while maintaining data confidentiality.
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,Event-Based Visual Sensing for Human Motion Detection and Classification at Various Distances,obtained at different depths and lighting conditions from the training set. We also show that having an Region of Interest detection leads to better accuracy compare to a full frame model on untrained distances.
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