Machine Learning In Document Analysis And Recognition

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Machine Learning In Document Analysis And Recognition
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Author : Simone Marinai
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-10
Machine Learning In Document Analysis And Recognition written by Simone Marinai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-10 with Computers categories.
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.
Handbook Of Character Recognition And Document Image Analysis
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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 1997
Handbook Of Character Recognition And Document Image Analysis written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
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 Processing Using Machine Learning
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Author : Sk Md Obaidullah
language : en
Publisher: CRC Press
Release Date : 2019-11-25
Document Processing Using Machine Learning written by Sk Md Obaidullah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-25 with Computers categories.
Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.
Deep Learning For Radar And Communications Automatic Target Recognition
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Author : Uttam K. Majumder
language : en
Publisher: Artech House
Release Date : 2020-07-31
Deep Learning For Radar And Communications Automatic Target Recognition written by Uttam K. Majumder and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Technology & Engineering categories.
This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
Deep Learning For Nlp And Speech Recognition
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Document Analysis And Recognition Icdar 2021 Workshops
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Author : Elisa H. Barney Smith
language : en
Publisher: Springer Nature
Release Date : 2021-09-03
Document Analysis And Recognition Icdar 2021 Workshops written by Elisa H. Barney Smith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-03 with Computers categories.
This book constitutes the proceedings of the international workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland, in September 2021.The total of 59 full and 12 short papers presented in this book were carefully selected from 96 submissions and divided into two volumes. Part II contains 30 full and 8 short papers that stem from the following meetings: Workshop on Machine Learning (WML); Workshop on Open Services and Tools for Document Analysis (OST); Workshop on Industrial Applications of Document Analysis and Recognition (WIADAR); Workshop on Computational Paleography (IWCP); Workshop on Document Images and Language (DIL); Workshop on Graph Representation Learning for Scanned Document Analysis (GLESDO).
Decision Forests
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Author : Antonio Criminisi
language : en
Publisher: Now Pub
Release Date : 2012-04-01
Decision Forests written by Antonio Criminisi and has been published by Now Pub this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-01 with Computers categories.
Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis.
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques
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Author : Olivas, Emilio Soria
language : en
Publisher: IGI Global
Release Date : 2009-08-31
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques written by Olivas, Emilio Soria and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Computers categories.
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Machine Learning Theory And Applications
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Author :
language : en
Publisher: Newnes
Release Date : 2013-05-16
Machine Learning Theory And Applications written by and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-16 with Computers categories.
Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security. - Very relevant to current research challenges faced in various fields - Self-contained reference to machine learning - Emphasis on applications-oriented techniques
Machine Learning Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2011-07-31
Machine Learning Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-31 with Computers categories.
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe