DocumentCode :
3099128
Title :
Applying a Weighting Matrix to the Hierarchical Neural Network Model for Handwritten Thai Character Recognition
Author :
Thammano, Arit ; Poolsamran, Patcharawadee
Author_Institution :
Comput. Intell. Lab., King Mongkut´´s Inst. of Technol. Ladkrabang, Bangkok
fYear :
2006
fDate :
Nov. 28 2006-Dec. 1 2006
Firstpage :
85
Lastpage :
85
Abstract :
This paper proposes a new neural network approach to the off-line handwritten Thai character recognition. This new neural network is a hierarchical neural network; it employs the concept of a weighting matrix in measuring the similarity between the incoming input pattern and the reference patterns. The experiments have been conducted to recognize both slipshod and proper handwritten characters. The results demonstrate a very promising performance of the proposed approach.
Keywords :
feedforward neural nets; handwritten character recognition; Thai characters; feedforward neural networks; hierarchical neural network; offline handwritten recognition; similarity measurement; weighting matrix; Character recognition; Computational intelligence; Electronic mail; Feature extraction; Handwriting recognition; Image segmentation; Information technology; Laboratories; Neural networks; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7695-2731-0
Type :
conf
DOI :
10.1109/CIMCA.2006.50
Filename :
4052724
Link To Document :
بازگشت