Document Processing Using Machine Learning
1st Edition
Published on 2. December 2019
Book
Hardback
168 pages
978-0-367-21847-8 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Illustrations
97 s/w Abbildungen, 47 s/w Tabellen
47 Tables, black and white; 97 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 15 mm
Weight
446 gr
ISBN-13
978-0-367-21847-8 (9780367218478)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Sk Md Obaidullah | KC Santosh | Teresa Goncalves
Document Processing Using Machine Learning
E-Book
11/2019
1st Edition
Chapman & Hall/CRC
€73.49
Available for download
Sk Md Obaidullah | KC Santosh | Teresa Goncalves
Document Processing Using Machine Learning
E-Book
11/2019
1st Edition
Chapman & Hall/CRC
€73.49
Available for download
Persons
Sk Md Obaidullah, KC Santosh, Teresa Goncalves, Nibaran Das, Kaushik Roy
Content
Preface
Editors
Contributors
1. Artificial Intelligence for Document Image Analysis
Himadri Mukherjee, Payel Rakshit, Ankita Dhar, Sk Md Obaidullah, KC Santosh, Santanu Phadikar and Kaushik Roy
2. An Approach toward Character Recognition of Bangla Handwritten Isolated Characters
Payel Rakshit, Chayan Halder and Kaushik Roy
3. Artistic Multi-Character Script Identification
Mridul Ghosh, Himadri Mukherjee, Sk Md Obaidullah, KC Santosh, Nibaran Das and Kaushik Roy
4. A Study on the Extreme Learning Machine and Its Applications
Himadri Mukherjee, Sahana Das, Subhashmita Ghosh, Sk Md Obaidullah, KC Santosh, Nibaran Das and Kaushik Roy
5. A Graph-Based Text Classification Model for Web Text Documents
Ankita Dhar, Niladri Sekhar Dash and Kaushik Roy
6. A Study of Distance Metrics in Document Classification
Ankita Dhar, Niladri Sekhar Dash and Kaushik Roy
7. A Study of Proximity of Domains for Text Categorization
Ankita Dhar, Niladri Sekhar Dash and Kaushik Roy
8. Supervised Learning for Aggression Identification and Author Profiling over Twitter Dataset
Kashyap Raiyani and Roy Bayot
9. The Effect of Using Features Computed from Generated Offline Images for Online Bangla Handwritten Character Recognition
Shibaprasad Sen, Ankan Bhattacharyya and Kaushik Roy
10. Handwritten Character Recognition for Palm-Leaf Manuscripts
Papangkorn Inkeaw, Jeerayut Chaijaruwanich and Jakramate Bootkrajang
Index
Editors
Contributors
1. Artificial Intelligence for Document Image Analysis
Himadri Mukherjee, Payel Rakshit, Ankita Dhar, Sk Md Obaidullah, KC Santosh, Santanu Phadikar and Kaushik Roy
2. An Approach toward Character Recognition of Bangla Handwritten Isolated Characters
Payel Rakshit, Chayan Halder and Kaushik Roy
3. Artistic Multi-Character Script Identification
Mridul Ghosh, Himadri Mukherjee, Sk Md Obaidullah, KC Santosh, Nibaran Das and Kaushik Roy
4. A Study on the Extreme Learning Machine and Its Applications
Himadri Mukherjee, Sahana Das, Subhashmita Ghosh, Sk Md Obaidullah, KC Santosh, Nibaran Das and Kaushik Roy
5. A Graph-Based Text Classification Model for Web Text Documents
Ankita Dhar, Niladri Sekhar Dash and Kaushik Roy
6. A Study of Distance Metrics in Document Classification
Ankita Dhar, Niladri Sekhar Dash and Kaushik Roy
7. A Study of Proximity of Domains for Text Categorization
Ankita Dhar, Niladri Sekhar Dash and Kaushik Roy
8. Supervised Learning for Aggression Identification and Author Profiling over Twitter Dataset
Kashyap Raiyani and Roy Bayot
9. The Effect of Using Features Computed from Generated Offline Images for Online Bangla Handwritten Character Recognition
Shibaprasad Sen, Ankan Bhattacharyya and Kaushik Roy
10. Handwritten Character Recognition for Palm-Leaf Manuscripts
Papangkorn Inkeaw, Jeerayut Chaijaruwanich and Jakramate Bootkrajang
Index