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Titlebook: Document Analysis Systems; 14th IAPR Internatio Xiang Bai,Dimosthenis Karatzas,Daniel Lopresti Conference proceedings 2020 Springer Nature

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書目名稱Document Analysis Systems
副標(biāo)題14th IAPR Internatio
編輯Xiang Bai,Dimosthenis Karatzas,Daniel Lopresti
視頻videohttp://file.papertrans.cn/283/282299/282299.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Document Analysis Systems; 14th IAPR Internatio Xiang Bai,Dimosthenis Karatzas,Daniel Lopresti Conference proceedings 2020 Springer Nature
描述.This book constitutes the refereed proceedings of the 14th IAPR International Workshop on Document Analysis Systems, DAS 2020, held in Wuhan, China, in July 2020...The 40 full papers presented in this book were carefully reviewed and selected from 57 submissions. The papers are grouped in the following topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text detection; and font design and classification..Due to the Corona pandemic the conference was held as a virtual event ..
出版日期Conference proceedings 2020
關(guān)鍵詞deep learning for document analysis systems; document analysis systems; historical document analysis; d
版次1
doihttps://doi.org/10.1007/978-3-030-57058-3
isbn_softcover978-3-030-57057-6
isbn_ebook978-3-030-57058-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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ALEC: An Accurate, Light and Efficient Network for CAPTCHA Recognitionplaced by depthwise separable convolutions to improve computational efficiency. The architecture utilizes group convolution and convolution channels reduction to build a deep narrow network, which reduces the model parameters and improves generalization performance. Additionally, effective and effic
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Background Removal of French University Diplomasd. So, we propose an approach for the separation of textual and non-textual components, based on Fuzzy C-Means clustering. After obtaining clustered pixels, a local window based thresholding approach and the Savoula binarization technique is used to correctly classify pixels, into the category of te
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