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Proceedings Paper

Character recognition by synergetic neural network based on selective attention parameters
Author(s): Mingxiang Wang; Yulong Mo; Junli Ma
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Paper Abstract

In this paper a learning algorithm of synergetic neural network based on selective attention parameters is proposed. According to the mechanism of the Human Visual System (HVS), the weight matrix of synergetic neural network can be obtained by multiplying the prototype matrix by selective attention parameters. Two selective attention models based on the human visual system are put forward in this paper. The comparative experiments between the traditional algorithm SCAP and the new method we proposed in the application of recognizing the real gray images of numeric and alphabetic characters are done. And the results show that our method can improve the synergetic neural network's recognition performance and be more suitable to human visual system.

Paper Details

Date Published: 25 March 2003
PDF: 6 pages
Proc. SPIE 5015, Applications of Artificial Neural Networks in Image Processing VIII, (25 March 2003); doi: 10.1117/12.477402
Show Author Affiliations
Mingxiang Wang, Shanghai Univ. (China)
Yulong Mo, Shanghai Univ. (China)
Junli Ma, Shanghai Univ. (China)


Published in SPIE Proceedings Vol. 5015:
Applications of Artificial Neural Networks in Image Processing VIII
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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