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Applying a Weighting Matrix to the Hierarchical Neural Network Model for Handwritten Thai Character Recognition
Sydney Australia November 28-December 01
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIMCA.2006.50International Conference on Computati ...
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Arit Thammano, King Mongkut's Institute of Technology Ladkrabang, Thailand
Patcharawadee Poolsamran, King Mongkut's Institute of Technology Ladkrabang, Thailand
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.
Citation:
Arit Thammano, Patcharawadee Poolsamran, "Applying a Weighting Matrix to the Hierarchical Neural Network Model for Handwritten Thai Character Recognition," cimca, pp.85, International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06), 2006
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