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Titlebook: Document Analysis and Recognition; 4th Workshop, DAR 20 Suresh Sundaram,Gaurav Harit Conference proceedings 2019 Springer Nature Singapore

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发表于 2025-3-21 19:51:54 | 显示全部楼层 |阅读模式
书目名称Document Analysis and Recognition
副标题4th Workshop, DAR 20
编辑Suresh Sundaram,Gaurav Harit
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Document Analysis and Recognition; 4th Workshop, DAR 20 Suresh Sundaram,Gaurav Harit Conference proceedings 2019 Springer Nature Singapore
描述1.    This book constitutes the refereed proceedings of the 4th Workshop on Document Analysis and Recognition, DAR 2018, held in Conjunction with ICVGIP 2018, in Hyderabad, India, in December 2018. The 12 revised full papers and 2 short papers presented were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections: document layout analysis and understanding; handwriting recognition and symbol spotting; character and word segmentation; handwriting analysis; datasets and performance evaluation.
出版日期Conference proceedings 2019
关键词artificial intelligence; character recognition; image analysis; image segmentation; optical character re
版次1
doihttps://doi.org/10.1007/978-981-13-9361-7
isbn_softcover978-981-13-9360-0
isbn_ebook978-981-13-9361-7Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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Document Analysis and Recognition978-981-13-9361-7Series ISSN 1865-0929 Series E-ISSN 1865-0937
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https://doi.org/10.1057/9781137355560 of a form processing system, namely touching component separation, text non-text separation and handwritten-printed text separation. The proposed method is evaluated on a database having 50 filled-in forms written in Bangla, collected during an essay competition in a school. The experimental results are promising.
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https://doi.org/10.1057/9781137486776 line detection, paragraph detection, word recognition, layout analysis etc. require pixel level annotation. In this paper, a Multi-layered Document Image Annotation System (MultiDIAS) has been introduced. The proposed system simultaneously provide a platform for hierarchical and pixel level annotat
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https://doi.org/10.1057/9781137355560 of a form processing system, namely touching component separation, text non-text separation and handwritten-printed text separation. The proposed method is evaluated on a database having 50 filled-in forms written in Bangla, collected during an essay competition in a school. The experimental result
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Ways to Social Integration of Women in MENAntry like India. Research on automation for the recognition of such handwritten forms has become mandatory. This applies more for a multilingual country like India. In the present work, we use readily available pre-trained Convolutional Neural Network (CNN) architectures on four different Indic scri
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Transitions to Early Care and Educationline handwritten Bangla characters. FD based feature computation starts with dividing a character sample into different rectangular zones. Then FD values are computed from each zone to every other zones. In distance based feature extraction technique also a character sample is divided into several s
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