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Titlebook: Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications; 6th International Co Reneta P. Barneva,Vale

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書目名稱Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications
副標(biāo)題6th International Co
編輯Reneta P. Barneva,Valentin E. Brimkov,Jo?o Manuel
視頻videohttp://file.papertrans.cn/233/232824/232824.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications; 6th International Co Reneta P. Barneva,Vale
描述.This book constitutes the refereed post-conference proceedings of the?6th International Symposium on Computational Modeling of Objects?Presented in Images, CompIMAGE 2018, held in Cracow, Poland, in.July 2018..The 16 revised full papers presented in this book were?carefully reviewed and selected from 30 submissions. The papers cover?the following topics: digital geometry; digital tomography; and methods and applications..
出版日期Conference proceedings 2019
關(guān)鍵詞image processing; image reconstruction; medical imaging; digital geometry; digital topology; digital tomo
版次1
doihttps://doi.org/10.1007/978-3-030-20805-9
isbn_softcover978-3-030-20804-2
isbn_ebook978-3-030-20805-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Conference proceedings 2019mages, CompIMAGE 2018, held in Cracow, Poland, in.July 2018..The 16 revised full papers presented in this book were?carefully reviewed and selected from 30 submissions. The papers cover?the following topics: digital geometry; digital tomography; and methods and applications..
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Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications978-3-030-20805-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
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List of symbols and abbreviations,ch can significantly affect the quality of reconstructions. We apply sequential feature selection methods to find the ‘most informative’ projection set based on a blueprint image. Using various software phantom images, we show that these methods outperform the previously published projection selection algorithms.
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