Document Analysis Systems II

Document Analysis Systems II

Author: Jonathan J. Hull

Publisher: World Scientific

Published: 1998

Total Pages: 542

ISBN-13: 9789810231033

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This book provides an overview of the state of the art in research and development of systems for document image analysis. Topics covered include a variety of systems and architectures for processing document images as well as methods for converting those images into formats that can be manipulated by a computer. The chapters are written by recognized experts in the field and describe Systems and Architectures, Recognition Techniques, Graphics Analysis, Document Image Retrieval, and World Wide Web Applications.


Document Analysis Systems

Document Analysis Systems

Author: Xiang Bai

Publisher: Springer Nature

Published: 2020-08-14

Total Pages: 588

ISBN-13: 3030570584

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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 .


Document Analysis Systems V

Document Analysis Systems V

Author: Daniel Lopresti

Publisher: Springer

Published: 2003-08-02

Total Pages: 582

ISBN-13: 3540458697

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This book constitutes the refereed proceedings of the 5th International Workshop on Document Analysis Systems, DAS 2002, held in Princeton, NJ, USA in August 2002 with sponsorship from IAPR.The 44 revised full papers presented together with 14 short papers were carefuly reviwed and selected for inclusion in the book. All current issues in document analysis systems are adressed. The papers are organized in topical sections on OCR features and systems, handwriting recognition, layout analysis, classifiers and learning, tables and forms, text extraction, indexing and retrieval, document engineering, and new applications.


Document Image Analysis

Document Image Analysis

Author: Horst Bunke

Publisher: World Scientific

Published: 1994

Total Pages: 282

ISBN-13: 9810220464

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Interest in the automatic processing and analysis of document images has been rapidly increasing during the past few years. This book addresses the different subfields of document image analysis, including preprocessing and segmentation, form processing, handwriting recognition, line drawing and map processing, and contextual processing.


Machine Learning in Document Analysis and Recognition

Machine Learning in Document Analysis and Recognition

Author: Simone Marinai

Publisher: Springer Science & Business Media

Published: 2008-01-10

Total Pages: 435

ISBN-13: 3540762795

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The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR.


Document Analysis And Text Recognition: Benchmarking State-of-the-art Systems

Document Analysis And Text Recognition: Benchmarking State-of-the-art Systems

Author: Volker Margner

Publisher: World Scientific

Published: 2018-02-27

Total Pages: 303

ISBN-13: 9813229284

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The compendium presents the latest results of the most prominent competitions held in the field of Document Analysis and Text Recognition. It includes a description of the participating systems and the underlying methods on one hand and the datasets used together with evaluation metrics on the other hand. This volume also demonstrates with examples, how to organize a competition and how to make it successful. It will be an indispensable handbook to the document image analysis community.


Handbook of Document Image Processing and Recognition

Handbook of Document Image Processing and Recognition

Author: David Doermann

Publisher: Springer

Published: 2014-05-22

Total Pages: 1055

ISBN-13: 9780857298607

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The Handbook of Document Image Processing and Recognition is a comprehensive resource on the latest methods and techniques in document image processing and recognition. Each chapter provides a clear overview of the topic followed by the state of the art of techniques used – including elements of comparison between them – along with supporting references to archival publications, for those interested in delving deeper into topics addressed. Rather than favor a particular approach, the text enables the reader to make an informed decision for their specific problems.


Handbook Of Character Recognition And Document Image Analysis

Handbook Of Character Recognition And Document Image Analysis

Author: Horst Bunke

Publisher: World Scientific

Published: 1997-05-02

Total Pages: 851

ISBN-13: 9814500380

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Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.


Document Analysis and Recognition – ICDAR 2021

Document Analysis and Recognition – ICDAR 2021

Author: Josep Lladós

Publisher: Springer Nature

Published: 2021-09-04

Total Pages: 878

ISBN-13: 303086331X

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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports. The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding.