Arabic and Chinese handwriting recognition : SACH 2006 summit, College Park, MD, USA, September 27-28, 2006 : selected papers / David Doermann, Stefan Jaeger (eds.)
The book constitutes the refereed proceedings of the Summit on Arabic and Chinese Handwriting Recognition, SACH 2006, held in College Park, USA, September 27-28, 2006. The 16 revised full papers presented were carefully reviewed and selected from a total of over 60 submissions. The first six papers...
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Other Authors: | , |
Other title: | SACH 2006. |
Format: | Conference Proceeding eBook |
Language: | English |
Published: |
Berlin ; New York :
Springer,
©2008.
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Series: | Lecture notes in computer science ;
4768. LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics. |
Subjects: |
Table of Contents:
- 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.