Arabic and Chinese Handwriting Recognition Summit, SACH 2006, College Park, MD, USA, September 27-28, 2006, Selected Papers /
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 Docu...
Corporate Author: | |
---|---|
Other Authors: | , |
Language: | English |
Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2008.
|
Edition: | 1st ed. 2008. |
Series: | Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
4768 |
Subjects: | |
Online Access: | https://doi.org/10.1007/978-3-540-78199-8 |
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.