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Advances In Digital Document Processing And Retrieval (statistical Science And Interdisciplinary Research) [Hardcover]

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  • Category: Books (Computers)
  • Author:  Bidyut Baran Chaudhuri, Swapan Kumar Parui
  • Author:  Bidyut Baran Chaudhuri, Swapan Kumar Parui
  • ISBN-10:  9814368709
  • ISBN-10:  9814368709
  • ISBN-13:  9789814368704
  • ISBN-13:  9789814368704
  • Publisher:  World Scientific Publishing Company
  • Publisher:  World Scientific Publishing Company
  • Pages:  336
  • Pages:  336
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Jun-2013
  • Pub Date:  01-Jun-2013
  • SKU:  9814368709-11-MPOD
  • SKU:  9814368709-11-MPOD
  • Item ID: 105502071
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Oct 01 to Oct 03
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.
From the participation of researchers in most important international conferences in the field, it is noted that activities in automatic document processing have been continuously growing. This book is an edited volume in Digital Document Processing where the chapters are written by several internationally renowned researchers in the domain. It will be useful for both students and researchers working on various aspects of document image analysis and recognition problems. It contains chapters on topics that are not covered by any textbook, but are more futuristic like Going beyond the Myth of Paperlessness , or interesting application areas like The Role of Document Image Analysis in Trustworthy Elections as well as Word Recognition for Museum Index Cards with SNT-Grid . Persons developing document analysis software for industry may also find the chapters useful and attractive. The language of the chapters is simple and clear, along with drawings/diagrams wherever necessary. An adequate number of references are given at the end of each chapter. Overall, the book is highly readable and will be an asset to the community. Renowned contributors include George Nagy, Hiromichi Fujisawa, F Kimura, D Lopresti, Chew Lim Tan, S Uchida, Thierry Paquet, Laurent Heutte, V Govindaraju and R Manmatha.

Readership: Engineers & technologists, statisticians, mathematicians and librarians.

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