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E-raamat: Document Processing Using Machine Learning [Taylor & Francis e-raamat]

Edited by , Edited by (University of South Dakota (USD), South Dakota, US), Edited by , Edited by , Edited by
  • Formaat: 168 pages, 47 Tables, black and white; 97 Illustrations, black and white
  • Ilmumisaeg: 02-Dec-2019
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-13: 9780429277573
  • Taylor & Francis e-raamat
  • Hind: 203,11 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 290,16 €
  • Säästad 30%
  • Formaat: 168 pages, 47 Tables, black and white; 97 Illustrations, black and white
  • Ilmumisaeg: 02-Dec-2019
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-13: 9780429277573

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.

Preface vii
Editors ix
Contributors xiii
1 Artificial Intelligence for Document Image Analysis
1(14)
Himadri Mukherjee
Payel Rakshit
Ankita Dinar
Sk Md Obaidullah
K.C. Santosh
Santanu Phadikar
Kaushik Roy
2 An Approach toward Character Recognition of Bangla Handwritten Isolated Characters
15(14)
Payel Rakshit
Chayan Halder
Kaushik Roy
3 Artistic Multi-Character Script Identification
29(14)
Mridul Ghosh
Himadri Mukherjee
Sk Md Obaidullah
K.C. Santosh
Nibaran Das
Kaushik Roy
4 A Study on the Extreme Learning Machine and Its Applications
43(10)
Himadri Mukherjee
Sahana Das
Subhashmita Ghosh
Sk Md Obaidullah
K.C. Santosh
Nibaran Das
Kaushik Roy
5 A Graph-Based Text Classification Model for Web Text Documents
53(16)
Ankita Dhar
Niladri Sekhar Dash
Kaushik Roy
6 A Study of Distance Metrics in Document Classification
69(16)
Ankita Dhar
Niladri Sekhar Dash
Kaushik Roy
7 A Study of Proximity of Domains for Text Categorization
85(16)
Ankita Dhar
Niladri Sekhar Dash
Kaushik Roy
8 Supervised Learning for Aggression Identification and Author Profiling over Twitter Dataset
101(20)
Kashyap Raiyani
Roy Bayot
9 The Effect of Using Features Computed from Generated Offline Images for Online Bangla Handwritten Character Recognition
121(24)
Shibaprasad Sen
Ankan Bhattacharyya
Kaushik Roy
10 Handwritten Character Recognition for Palm-Leaf Manuscripts
145(18)
Papangkorn Inkeaw
Jeerayut Chaijaruwanich
Jakramate Bootkrajang
Index 163
Sk Md Obaidullah, KC Santosh, Teresa Goncalves, Nibaran Das, Kaushik Roy