Document Processing Using Machine Learning (inbunden)
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Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
168
Utgivningsdatum
2019-12-02
Förlag
Chapman & Hall/CRC
Illustratör/Fotograf
black and white 97 Illustrations 47 Tables black and white
Illustrationer
47 Tables, black and white; 97 Illustrations, black and white
Dimensioner
239 x 157 x 15 mm
Vikt
363 g
Antal komponenter
1
ISBN
9780367218478
Document Processing Using Machine Learning (inbunden)

Document Processing Using Machine Learning

av Sk Md Obaidullah, Kc Santosh, Teresa Goncalves, Nibaran Das, Kaushik Roy
Inbunden,  Engelska, 2019-12-02
1926

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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.
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Sk Md Obaidullah, Kc Santosh, Teresa Goncalves, Nibaran Das, Kaushik Roy

Övrig information

Sk Md Obaidullah, KC Santosh, Teresa Goncalves, Nibaran Das, Kaushik Roy

Innehållsförteckning

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

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