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Titlebook: Computer Analysis of Images and Patterns; 14th International C Pedro Real,Daniel Diaz-Pernil,Walter Kropatsch Conference proceedings 2011 S

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發(fā)表于 2025-3-21 18:59:44 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computer Analysis of Images and Patterns
副標(biāo)題14th International C
編輯Pedro Real,Daniel Diaz-Pernil,Walter Kropatsch
視頻videohttp://file.papertrans.cn/234/233446/233446.mp4
概述Fast-track conference proceedings.State-of-the-art research.Up-to-date results
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Analysis of Images and Patterns; 14th International C Pedro Real,Daniel Diaz-Pernil,Walter Kropatsch Conference proceedings 2011 S
描述The two volume set LNCS 6854/6855 constitutes the refereed proceedings of the International Conference on Computer Analysis of Images and Patterns, CAIP 2011,which took place in Seville, Spain, August 29-31, 2011. The 138 papers presented together with 2 invited talks were carefully reviewed and selected from 286 submissions. The papers are organized in topical section on: motion analysis, image and shape models, segmentation and grouping, shape recovery, kernel methods, medical imaging, structural pattern recognition, Biometrics, image and video processing, calibration; and tracking and stereo vision.
出版日期Conference proceedings 2011
關(guān)鍵詞biometric recognition; digital imaging; document recognition; image analysis; medical image processing
版次1
doihttps://doi.org/10.1007/978-3-642-23678-5
isbn_softcover978-3-642-23677-8
isbn_ebook978-3-642-23678-5Series 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Computer Analysis of Images and Patterns影響因子(影響力)




書目名稱Computer Analysis of Images and Patterns影響因子(影響力)學(xué)科排名




書目名稱Computer Analysis of Images and Patterns網(wǎng)絡(luò)公開度




書目名稱Computer Analysis of Images and Patterns網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Analysis of Images and Patterns被引頻次




書目名稱Computer Analysis of Images and Patterns被引頻次學(xué)科排名




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書目名稱Computer Analysis of Images and Patterns年度引用學(xué)科排名




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書目名稱Computer Analysis of Images and Patterns讀者反饋學(xué)科排名




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C. Dellacherie,P. A. Meyer,M. Yorlogy with the picture database of missing persons, the identity of an unknown skull can be determined. In this paper, we propose a method to quantitatively analyze the quality of the facial landmarks for skull identification. Based on the quality analysis of landmarks, a new landmark-based algorithm
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Domains of attraction in Banach spaces,ntial integration of multi-instance and multi-sample fusion schemes allows controlled trade-off between false alarms and false rejects. Expressions for each type of error for the fused system have previously been derived for the case of statistically independent classifier decisions. It is shown in
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,Une remarque sur l’expose precedent,e performance of facial point localization is to use the spatial relation between facial feature positions. While existing algorithms mostly rely on the priori knowledge of facial structure and on a training phase, this paper presents an online approach without requirements of pre-defined constraint
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https://doi.org/10.1007/BFb0070846 and comparing dental features from digital radiograms was developed by the creators of Automated Dental Identification System (ADIS). In this paper, a novel method of extracting teeth shapes from extraoral radiograms, known as orthopantomograms, is proposed. The method segments the image using the
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C. S. Chou,P. A. Meyer,C. StrickerBSS) method for nonnegative and correlated data. A major approach to non-negative BSS relies on a strict non-overlap condition (also known as the pixel purity assumption in hyper-spectral imaging) of source signals which is not always guaranteed in the NMR spectra of chemical compounds. A new domina
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Prolongement des semimartingales,is proposed for face recognition under different illumination conditions. The proposed approach applies Difference of Gaussian (DoG) filter in the logarithm domain of face images. LBPs are extracted from the filtered images and used for recognition. A novel measurement is also proposed to calculate
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