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Titlebook: Computer Analysis of Images and Patterns; 18th International C Mario Vento,Gennaro Percannella Conference proceedings 2019 Springer Nature

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書目名稱Computer Analysis of Images and Patterns
副標題18th International C
編輯Mario Vento,Gennaro Percannella
視頻videohttp://file.papertrans.cn/234/233440/233440.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Analysis of Images and Patterns; 18th International C Mario Vento,Gennaro Percannella Conference proceedings 2019 Springer Nature
描述.The two volume set LNCS 11678 and 11679 constitutes the refereed proceedings of the 18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019...The 106 papers presented were carefully reviewed and selected from 176 submissions The papers are organized in the following topical sections: Intelligent Systems; Real-time and GPU Processing; Image Segmentation; Image and Texture Analysis; Machine Learning for Image and Pattern Analysis; Data Sets and Benchmarks; Structural and Computational Pattern Recognition; Posters..
出版日期Conference proceedings 2019
關(guān)鍵詞artificial intelligence; classification; computer vision; descriptors; digital image; estimation; Human-Co
版次1
doihttps://doi.org/10.1007/978-3-030-29888-3
isbn_softcover978-3-030-29887-6
isbn_ebook978-3-030-29888-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
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




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,Groupes à croissance polynomiale, estimate 3D human poses from a monocular camera. To show the validity of our method, we propose a 3D skeleton-based two-stage action detection approach. For localizing actions in unsegmented sequences, Relative Joint Position (RJP) and Histogram Of Displacements (HOD) are used as inputs to a k-near
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https://doi.org/10.1007/BFb0059240hen studying Inorganic nanoparticles using TEM is the automated analysis of the images, i.e. segmentation of individual nanoparticles. The current state-of-the-art methods generally rely on binarization routines that require parameterization, and on methods to segment the overlapping nanoparticles (
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