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Titlebook: Image Analysis and Recognition; 12th International C Mohamed Kamel,Aurélio Campilho Conference proceedings 2015 Springer International Publ

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發(fā)表于 2025-3-21 17:50:13 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Image Analysis and Recognition
副標(biāo)題12th International C
編輯Mohamed Kamel,Aurélio Campilho
視頻videohttp://file.papertrans.cn/462/461395/461395.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Image Analysis and Recognition; 12th International C Mohamed Kamel,Aurélio Campilho Conference proceedings 2015 Springer International Publ
描述This book constitutes the thoroughly refereed proceedings of the 12th International Conference on Image Analysis and Recognition, ICIAR 2015, held in Niagara Falls, ON, Canada, in July 2015. The 55 revised full papers and 5 short papers presented were carefully reviewed and selected from 80 submissions. The papers are organized in the following topical sections: image quality assessment; image enhancement; image segmentation, registration and analysis; image coding, compression and encryption; dimensionality reduction and classification; biometrics; face description, detection and recognition; human activity recognition; robotics and 3D vision; medical image analysis; and applications.
出版日期Conference proceedings 2015
關(guān)鍵詞biomedical; biometric; character recognition; classification; clustering; computer vision; image enhanceme
版次1
doihttps://doi.org/10.1007/978-3-319-20801-5
isbn_softcover978-3-319-20800-8
isbn_ebook978-3-319-20801-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Label Fusion for Multi-atlas Segmentation Based on Majority Votingver-segmentation problem of the majority fusion. The approach is successfully applied to the segmentation of hippocampus, and the experimental results demonstrate significant improvement over three state-of-the-art approaches in the literature.
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An Optimized Selective Encryption for Video Confidentialityof simulation on different video sequences indicate that the derived set of QC’s can reduce ECO cost by up?to 78?% without affecting the video confidentiality when compared to state-of-the-art approaches.
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Attributed Relational Graph-Based Learning of Object Models for Object Segmentationontains an instance of the OOI, is given. Afterwards, each image is over-segmented into a set of visually homogeneous regions and the corresponding ARG is constructed. Given such graph representations, OOI model learning reduces to a subgraph matching problem.
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