Arabic and Chinese Handwriting Recognition: Summit, SACH 2006, College Park, MD, USA, September 27-28, 2006, Selected Papers: Lecture Notes in Computer Science, cartea 4768
Editat de David Doermann, Stefan Jaegeren Limba Engleză Paperback – 3 apr 2008
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Specificații
ISBN-13: 9783540781981
ISBN-10: 3540781986
Pagini: 296
Ilustrații: VIII, 279 p.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.45 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540781986
Pagini: 296
Ilustrații: VIII, 279 p.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.45 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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.