Atjaunināt sīkdatņu piekrišanu

Arabic and Chinese Handwriting Recognition: Summit, SACH 2006, College Park, MD, USA, September 27-28, 2006, Selected Papers 2008 ed. [Mīkstie vāki]

Edited by , Edited by
  • Formāts: Paperback / softback, 279 pages, height x width: 235x155 mm, weight: 456 g, VIII, 279 p., 1 Paperback / softback
  • Sērija : Image Processing, Computer Vision, Pattern Recognition, and Graphics 4768
  • Izdošanas datums: 03-Apr-2008
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540781986
  • ISBN-13: 9783540781981
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 46,91 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 55,19 €
  • Ietaupiet 15%
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Formāts: Paperback / softback, 279 pages, height x width: 235x155 mm, weight: 456 g, VIII, 279 p., 1 Paperback / softback
  • Sērija : Image Processing, Computer Vision, Pattern Recognition, and Graphics 4768
  • Izdošanas datums: 03-Apr-2008
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540781986
  • ISBN-13: 9783540781981
Citas grāmatas par šo tēmu:
In the fall of 2006, the University of Maryland, along with various government and industrial sponsors, invited leading researchers from all over the world to a two-day Summit on Arabic and Chinese Handwriting Recognition (SACH 2006). The event acted as a complement to the biennial Symposium on Document Image Understanding Technology (SDIUT), providing a focused glimpse into the state of the art in Arabic and Chinese handwriting recognition. It offered a forum for interaction with prominent researchers at the forefront of the scientific community and provided an opportunity for participants to help explore possible directions of the field. This book is a result of the expansion, peer review, and revision of selected papers presented at this meeting. Handwriting recognition remains the Holy Grail of document analysis, and Arabic and Chinese scripts embrace many of the most significant challenges. We are pleased to have 16 scientific papers covering the original topics of handwritten Arabic and Chinese, as well as 2 papers covering other handwritten scripts. We asked each author to not only describe the techniques used in addressing the problem, but to attempt to identify the key research challenges and problems that the community faces. The result is an impressive collection of manuscripts that provide various detailed views of the state of research. In this book, six articles deal directly with Arabic handwriting. Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.
Visual Recognition of Arabic Handwriting: Challenges and New
Directions.- A Review on Persian Script and Recognition Techniques.- Human
Reading Based Strategies for Off-Line Arabic Word Recognition.- Versatile
Search of Scanned Arabic Handwriting.- A Two-Tier Arabic Offline Handwriting
Recognition Based on Conditional Joining Rules.- Databases and Competitions:
Strategies to Improve Arabic Recognition Systems.- Handwritten Chinese
Character Recognition: Effects of Shape Normalization and Feature
Extraction.- How to Deal with Uncertainty and Variability: Experience and
Solutions.- An Efficient Candidate Set Size Reduction Method for
Coarse-Classification in Chinese Handwriting Recognition.- Techniques for
Solving the Large-Scale Classification Problem in Chinese Handwriting
Recognition.- Recent Results of Online Japanese Handwriting Recognition and
Its Applications.- Segmentation-Driven Offline Handwritten Chinese and Arabic
Script Recognition.- Multi-character Field Recognition for Arabic and Chinese
Handwriting.- Multi-lingual Offline Handwriting Recognition Using Hidden
Markov Models: A Script-Independent Approach.- Handwritten Character
Recognition of Popular South Indian Scripts.- Ensemble Methods to Improve the
Performance of an English Handwritten Text Line Recognizer.