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Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi

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发表于 2025-3-21 18:13:38 | 显示全部楼层 |阅读模式
书目名称Document Analysis and Recognition - ICDAR 2024
副标题18th International C
编辑Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng
视频videohttp://file.papertrans.cn/285/284810/284810.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi
描述.This six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024..The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions..The papers reflect topics such as: document image processing; physical and logical layout analysis; text and symbol recognition; handwriting recognition; document analysis systems; document classification; indexing and retrieval of documents; document synthesis; extracting document semantics; NLP for document understanding; office automation; graphics recognition; human document interaction; document representation modeling and much more... .
出版日期Conference proceedings 2024
关键词Document Analysis Systems; Handwriting Recognition; Scene Text Detection and Recognition; Document Imag
版次1
doihttps://doi.org/10.1007/978-3-031-70543-4
isbn_softcover978-3-031-70542-7
isbn_ebook978-3-031-70543-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/e/image/284810.jpg
发表于 2025-3-22 04:13:37 | 显示全部楼层
allenges of this task is that documents generally exhibit degradations and acquisition artifacts that can greatly vary throughout the page. Nonetheless, even when dealing with a local patch of the document, taking into account the overall appearance of a wide portion of the page can ease the predict
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ailability, and complex orthographic diacritics. The dataset consists of roughly 80,000 annotated text-line images from 1700 pages of . to . century documents, including a training set with text-line images from the . to . century and two test sets. One is distributed similarly to the training set w
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ion about individuals living in France and their households. We aim at extracting all the information contained in these tables using automatic handwritten table recognition. At the end of the Socface project, in which our work is taking place, the extracted information will be redistributed to the
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bution, scribe-papermaker relation, trading, etc.) in Humanities such as Musicology. As of today, they come in a variety of formats: digitized handtracings and rubbings, X-ray based imagery and, more recently, thermograms acquired with infrared (IR) cameras – all of which have been made accessible v
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tudy the diffusion of astronomical knowledge on a global scale. However, state-of-the-art vectorization methods, often designed to tackle modern data, are not adapted to the complexity and diversity of historical astronomical diagrams. Our contribution is thus twofold. First, we introduce a unique d
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of text, covering more than half of the 19th century (i.e., 1817) until the late part of the 20th century (i.e., 1990). Eight native Romanian speakers annotated the dataset with five named entities. The samples belong to one of the following four historical regions of Romania, namely Bessarabia, Mo
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