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Titlebook: Image and Graphics Technologies and Applications; 15th Chinese Confere Yongtian Wang,Xueming Li,Yuxin Peng Conference proceedings 2020 Spri

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书目名称Image and Graphics Technologies and Applications
副标题15th Chinese Confere
编辑Yongtian Wang,Xueming Li,Yuxin Peng
视频videohttp://file.papertrans.cn/462/461493/461493.mp4
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Image and Graphics Technologies and Applications; 15th Chinese Confere Yongtian Wang,Xueming Li,Yuxin Peng Conference proceedings 2020 Spri
描述This book constitutes the refereed proceedings of the 15th Conference on Image and Graphics Technologies and Applications, IGTA 2020, held in Beijing, China in September, 2020.*.The 24 papers presented were carefully reviewed and selected from 115 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR, as well as image technology applications...*The conference was held virtually due to the COVID-19 pandemic..
出版日期Conference proceedings 2020
关键词computer networks; computer security; computer systems; computer vision; face recognition; Human-Computer
版次1
doihttps://doi.org/10.1007/978-981-33-6033-4
isbn_softcover978-981-33-6032-7
isbn_ebook978-981-33-6033-4Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2020
The information of publication is updating

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/i/image/461493.jpg
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Accurate Estimation of Motion Blur Kernel Based on Genetic Algorithmsre developed for optimizing motion blur kernel. Effective fitness function and genetic operators are designed to ensure the convergence of the optimization process. Several traditional methods are compared with the proposed method. Real aerial image data sets are used to test the performance of thes
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Graph Embedding Discriminant Analysis and Semi-Supervised Extension for Face Recognitiones in practical applications and thus degrades the discriminant performance, a novel graph embedding discriminant analysis method and its semi-supervised extension for face recognition is proposed in this paper. It uses the intraclass samples and their within-class mean to construct the intrinsic gr
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