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Proceedings Paper

Hierarchical multilayer perceptron neural network for the recognition of the automobile license plate number
Author(s): Joongho Chang; Norman C. Griswold
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Paper Abstract

This paper proposes a new hierarchical multilayer perceptron (HMLP) network as an improved classifier for alpha-numeric character recognition from the automobile license plates. HMLP is built up by hierarchically stacking the small MLP subnetworks that work as local classifiers in the feature space. Each subnetwork is trained not to cause overtraining. The generalization and overtraining problem of neural networks was reduced by this method. The classification performance of HMLP was compared with the conventional single stage MLP, and HMLP showed better performance especially for the large sized classification problem.

Paper Details

Date Published: 4 March 1996
PDF: 7 pages
Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); doi: 10.1117/12.234249
Show Author Affiliations
Joongho Chang, Texas A&M Univ. (United States)
Norman C. Griswold, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 2664:
Applications of Artificial Neural Networks in Image Processing
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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