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Titlebook: Computer Analysis of Images and Patterns; 16th International C George Azzopardi,Nicolai Petkov Conference proceedings 2015 Springer Interna

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發(fā)表于 2025-3-21 19:14:30 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Computer Analysis of Images and Patterns
副標(biāo)題16th International C
編輯George Azzopardi,Nicolai Petkov
視頻videohttp://file.papertrans.cn/234/233437/233437.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Analysis of Images and Patterns; 16th International C George Azzopardi,Nicolai Petkov Conference proceedings 2015 Springer Interna
描述.The two volume set LNCS 9256 and 9257 constitutes the refereed proceedings of the 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015, held in Valletta, Malta, in September 2015. The 138 papers presented were carefully reviewed and selected from numerous submissions. CAIP 2015 is the sixteenth in the CAIP series of biennial international conferences devoted to all aspects of computer vision, image analysis and processing, pattern recognition, and related fields..
出版日期Conference proceedings 2015
關(guān)鍵詞3D reconstruction; Biometrics; Brain computer interfaces; Clustering; Data compression; Genetic algorithm
版次1
doihttps://doi.org/10.1007/978-3-319-23192-1
isbn_softcover978-3-319-23191-4
isbn_ebook978-3-319-23192-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
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




書目名稱Computer Analysis of Images and Patterns年度引用




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,Die Ern?hrung des neugeborenen Kindes,is proposed to detect occluded vehicles (occludees). First, we detect and track fully-visible vehicles (occluders). Occludee detection adopts those occluders as priors. Two classifiers for partially-visible vehicles are trained to use appearance cues. Disparity is adopted to further constrain the oc
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Arthur Keller,Chr. J. Klumker,O. Zieglervide robustness to viewpoint change but yield complex models. This paper shows that robustness with lighter models can be achieved through robust descriptors. A comparison between various descriptors allows choosing the one providing the best viewpoint robustness, in this case the ASIFT descriptor.
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https://doi.org/10.1007/978-3-642-52590-2here is a need to overcome the challenge to analyze all this large amount of visual data that users post in internet. We will address this analysis by providing a review on how to measure image and video interestingness and memorability from content that is tacked spontaneously in social networks. W
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https://doi.org/10.1007/978-3-7091-5322-2ion and Substitution. We present a method to learn the Insertion and Deletion costs of nodes and edges defined in the Graph Edit Distance, whereas, we define the Edit Cost Substitution data dependent and without parameters (for instance the Euclidean distance). In some applications, the ground truth
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