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
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