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Titlebook: Combinatorial Image Analysis; 19th International W Reneta P. Barneva,Valentin E. Brimkov,Jo?o Manuel Conference proceedings 2018 Springer

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書(shū)目名稱(chēng)Combinatorial Image Analysis
副標(biāo)題19th International W
編輯Reneta P. Barneva,Valentin E. Brimkov,Jo?o Manuel
視頻videohttp://file.papertrans.cn/230/229913/229913.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Combinatorial Image Analysis; 19th International W Reneta P. Barneva,Valentin E. Brimkov,Jo?o Manuel  Conference proceedings 2018 Springer
描述This book constitutes the refereed proceedings of the 19th International Workshop on Combinatorial Image Analysis, IWCIA 2018, held in Porto, Portugal, in November 2018..The 18 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are?grouped into two sections. The first one includes?nine papers devoted to theoretical foundations of combinatorial image analysis,?including digital geometry and topology, array grammars, tilings and patterns,?discrete geometry in non-rectangular grids, and other technical tools for image?analysis. The second part includes nine papers presenting application-driven?research on topics such as discrete tomography, image segmentation, texture?analysis, and medical imaging..
出版日期Conference proceedings 2018
關(guān)鍵詞3D; computer graphics; computer vision; image analysis; image processing; image reconstruction; image regi
版次1
doihttps://doi.org/10.1007/978-3-030-05288-1
isbn_softcover978-3-030-05287-4
isbn_ebook978-3-030-05288-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

書(shū)目名稱(chēng)Combinatorial Image Analysis影響因子(影響力)




書(shū)目名稱(chēng)Combinatorial Image Analysis影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Combinatorial Image Analysis網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Combinatorial Image Analysis網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Combinatorial Image Analysis被引頻次




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書(shū)目名稱(chēng)Combinatorial Image Analysis讀者反饋




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K. Dalziel,P. J. Dykes,R. Markse exploited by the reconstruction algorithm. In this paper we present Multi-Channel DART (MC-DART), which deals effectively with multi-channel data. This class of algorithms is a generalization of DART to multiple channels and combines the information for each separate channel-reconstruction in a mu
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N. A. Williams,W. A. Blyth,T. J. Hill 2D, based on the known connection between the number of 0-gaps and the Euler characteristic of 2D digital objects. We also present two new, short and intuitive proofs of one of the two known equivalent formulae for the number of .-gaps in .D digital objects.
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