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Titlebook: Document Analysis and Recognition – ICDAR 2024 Workshops; Athens, Greece, Augu Harold Mouchère,Anna Zhu Conference proceedings 2024 The Edi

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书目名称Document Analysis and Recognition – ICDAR 2024 Workshops
副标题Athens, Greece, Augu
编辑Harold Mouchère,Anna Zhu
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Document Analysis and Recognition – ICDAR 2024 Workshops; Athens, Greece, Augu Harold Mouchère,Anna Zhu Conference proceedings 2024 The Edi
描述.This two-volume set LNCS 14935-14936 constitutes the proceedings of International Workshops co-located with the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–31, 2024..The total of 30 regular papers presented in these proceedings were carefully selected from 46 submissions..Part I contains 16 regular papers that stem from the following workshops:..ICDAR 2024 Workshop on Automatically Domain-Adapted and Personalized Document Analysis (ADAPDA);..ICDAR 2024 Workshop on Advanced Analysis and Recognition of Parliamentary Corpora (ARPC);..ICDAR 2024 Workshop on coMics ANalysis, Processing and Understanding (MANPU)..Part II contains 14 regular papers that stem from the following workshops:..ICDAR 2024 Workshop on Computational Paleography (IWCP);..ICDAR 2024 Workshop on Machine Vision and NLP for Document Analysis (VINALDO)..
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/10.1007/978-3-031-70645-5
isbn_softcover978-3-031-70644-8
isbn_ebook978-3-031-70645-5Series 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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TrOCR Meets Language Models: An End-to-End Post-correction Approachmodel with a language model (LM) that serves as a corrector. This integration addresses three principal challenges: over-correction, which compromises text authenticity; poor domain adaptation; and the scarcity of annotated images. We explore the synergy between TrOCR, a state-of-the-art OCR model,
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: Domain Adaptive Document Restoration with a Layer Separation Approachaditional methods often falter with variable document types, leading to poor performance. To overcome these limitations, this paper introduces a text-graphic layer separation approach that enhances domain adaptability in document image restoration (DIR) systems. We propose ., which utilizes two laye
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Normalized vs Diplomatic Annotation: A Case Study of Automatic Information Extraction from Handwrittndwritten in Spanish. We investigate two annotation strategies for automatically transcribing handwritten documents, fine-tuning DAN with minimal training data and annotation effort. Experiments were conducted on two datasets containing the same images (201 scans of birth certificates written by mor
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Diminutives in Political Discourse – The Case of Serbian and Slovenianhis paper draws comparisons between the use of diminutives in the ParlaMint-RS 4.0 (Serbian parliament) and ParlaMint-SI 4.0 (Slovenian parliament) corpora [.]. Our findings reveal a distinctive pattern within political discussions: the employment of diminutives, particularly when referring to entit
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Retrieving and Analyzing Translations of American Newspaper Comics with Visual Evidencen comics’ text features, thereby largely ignoring comics’ heavily visual dimension. Image classification applications for comics focus primarily on genre and artist attribution. This paper bridges the gap between these areas by investigating image classification model accuracy for identifying transl
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