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Titlebook: Computational Visual Media; First International Shi-Min Hu,Ralph R. Martin Conference proceedings 2012 Springer-Verlag Berlin Heidelberg 2

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书目名称Computational Visual Media
副标题First International
编辑Shi-Min Hu,Ralph R. Martin
视频video
概述Fast track conference proceedings.Unique visibility.State of the art research
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computational Visual Media; First International  Shi-Min Hu,Ralph R. Martin Conference proceedings 2012 Springer-Verlag Berlin Heidelberg 2
描述This book constitutes the refereed proceedings of CVM 2012, the First International Conference on Computational Visual Media, held in Beijing, China, in November 2012. .The 33 revised full papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on image processing I and II, geometric processing, saliency, recognition, perception and learning, shape analysis, media retrieval, and capture, rendering and visualization.
出版日期Conference proceedings 2012
关键词combinatorial maps; geometric verification; image recognition; post-processing; virtual reality; algorith
版次1
doihttps://doi.org/10.1007/978-3-642-34263-9
isbn_softcover978-3-642-34262-2
isbn_ebook978-3-642-34263-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2012
The information of publication is updating

书目名称Computational Visual Media影响因子(影响力)




书目名称Computational Visual Media影响因子(影响力)学科排名




书目名称Computational Visual Media网络公开度




书目名称Computational Visual Media网络公开度学科排名




书目名称Computational Visual Media被引频次




书目名称Computational Visual Media被引频次学科排名




书目名称Computational Visual Media年度引用




书目名称Computational Visual Media年度引用学科排名




书目名称Computational Visual Media读者反馈




书目名称Computational Visual Media读者反馈学科排名




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https://doi.org/10.1007/978-0-387-75146-7 combining the Public Goods Game, our algorithm can efficiently solve the multi-label segmentation problem. Experiments on challenging datasets demonstrate that our algorithm outperforms the state-of-art. We believe that this algorithm can be extended to many other labeling problems.
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A Novel Customized Recompression Framework for Massive Internet Imagesompression. In this paper, we propose a novel framework to efficiently customize image recompression according to a variety of applications. And our new framework has been successfully applied to many commercial applications, such as web portals, e-commerce, online game and so on.
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A Game-Theoretical Approach to Image Segmentation combining the Public Goods Game, our algorithm can efficiently solve the multi-label segmentation problem. Experiments on challenging datasets demonstrate that our algorithm outperforms the state-of-art. We believe that this algorithm can be extended to many other labeling problems.
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0302-9743 viewed and selected from 81 submissions. The papers are organized in topical sections on image processing I and II, geometric processing, saliency, recognition, perception and learning, shape analysis, media retrieval, and capture, rendering and visualization.978-3-642-34262-2978-3-642-34263-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
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