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Titlebook: Image Analysis and Recognition; 8th International Co Mohamed Kamel,Aurélio Campilho Conference proceedings 2011 Springer-Verlag GmbH Berlin

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書目名稱Image Analysis and Recognition
副標(biāo)題8th International Co
編輯Mohamed Kamel,Aurélio Campilho
視頻videohttp://file.papertrans.cn/462/461389/461389.mp4
概述Up-to-date results.Fast-track conference proceedings.State-of-the-art research
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Image Analysis and Recognition; 8th International Co Mohamed Kamel,Aurélio Campilho Conference proceedings 2011 Springer-Verlag GmbH Berlin
描述The two-volume set LNCS 6753/6754 constitutes the refereed proceedings of the 8th International Conference on Image and Recognition, ICIAR 2011, held in Burnaby, Canada, in June 2011. The 84 revised full papers presented were carefully reviewed and selected from 147 submissions. The papers are organized in topical sections on image and video processing; feature extraction and pattern recognition; computer vision; color, texture, motion and shape; tracking; biomedical image analysis; biometrics; face recognition; image coding, compression and encryption; and applications.
出版日期Conference proceedings 2011
關(guān)鍵詞biometric recognition; fingerprint recognition; image metrics; machine learning; medical image processin
版次1
doihttps://doi.org/10.1007/978-3-642-21593-3
isbn_softcover978-3-642-21592-6
isbn_ebook978-3-642-21593-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2011
The information of publication is updating

書目名稱Image Analysis and Recognition影響因子(影響力)




書目名稱Image Analysis and Recognition影響因子(影響力)學(xué)科排名




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書目名稱Image Analysis and Recognition網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Image Analysis and Recognition被引頻次




書目名稱Image Analysis and Recognition被引頻次學(xué)科排名




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Hierarchical Spatial Matching Kernel for Image Categorizationrdinalities. In experiments, the results of HSMK outperformed those of SPM and led to state-of-the-art performance on several well-known databases of benchmarks in image categorization, even when using only a single type of feature.
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Classification of Atomic Density Distributions Using Scale Invariant Blob Localization The results presented here are restricted to special image structures occurring in the atom optics experiment, but the presented methodology can lead to improved results for a wide class of pattern recognition and blob localization problems.
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Conference proceedings 2011ized in topical sections on image and video processing; feature extraction and pattern recognition; computer vision; color, texture, motion and shape; tracking; biomedical image analysis; biometrics; face recognition; image coding, compression and encryption; and applications.
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