Advances in Document Image Analysis
Advances in Document Image Analysis

Author: Nabeel A. Murshed

Publisher: Springer Science & Business Media

Published: 1997-10-22

Total Pages: 364

ISBN-13: 9783540637912

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This book constitutes the refereed proceedings of the First Brazilian Symposium on Document Image Analysis, BSDIA'97, held in Curitiba in November 1997. The volume presents 19 revised full papers selected from 30 submissions as well as eight full-paper invited contributions by internationally leading authorities. The invited papers give a unique survey of the state of the art in the area. The selected papers are organized in sections on low level processing, document processing and retrieval, handwriting recognition, signature verification, and application systems.

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.

Digital Document Processing
Digital Document Processing

Author: Bidyut B. Chaudhuri

Publisher: Springer Science & Business Media

Published: 2007-03-13

Total Pages: 473

ISBN-13: 184628726X

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This book brings all the major and frontier topics in the field of document analysis together into a single volume, creating a unique reference source that will be invaluable to a large audience of researchers, lecturers and students working in this field. With chapters written by some of the most distinguished researchers active in this field, this book addresses recent advances in digital document processing research and development.

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.

Automatic Digital Document Processing and Management
Automatic Digital Document Processing and Management

Author: Stefano Ferilli

Publisher: Springer Science & Business Media

Published: 2011-01-03

Total Pages: 313

ISBN-13: 085729198X

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This text reviews the issues involved in handling and processing digital documents. Examining the full range of a document’s lifetime, the book covers acquisition, representation, security, pre-processing, layout analysis, understanding, analysis of single components, information extraction, filing, indexing and retrieval. Features: provides a list of acronyms and a glossary of technical terms; contains appendices covering key concepts in machine learning, and providing a case study on building an intelligent system for digital document and library management; discusses issues of security, and legal aspects of digital documents; examines core issues of document image analysis, and image processing techniques of particular relevance to digitized documents; reviews the resources available for natural language processing, in addition to techniques of linguistic analysis for content handling; investigates methods for extracting and retrieving data/information from a document.

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.

Document Image Processing
Document Image Processing

Author: Ergina Kavallieratou

Publisher: MDPI

Published: 2018-10-03

Total Pages: 217

ISBN-13: 3038971057

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This book is a printed edition of the Special Issue "Document Image Processing" that was published in J. Imaging

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.

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Author: Nilanjan Dey

Publisher: Academic Press

Published: 2019-07-31

Total Pages: 220

ISBN-13: 0128180056

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. - Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges - Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications - Introduces several techniques for medical image processing and analysis for CAD systems design