20 September 2001 Handwritten character recognition based on hybrid neural networks
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Proceedings Volume 4555, Neural Network and Distributed Processing; (2001) https://doi.org/10.1117/12.441669
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
Abstract
A hybrid neural network system for the recognition of handwritten character using SOFM,BP and Fuzzy network is presented. The horizontal and vertical project of preprocessed character and 4_directional edge project are used as feature vectors. In order to improve the recognition effect, the GAT algorithm is applied. Through the hybrid neural network system, the recognition rate is improved visibly.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peng Wang, Peng Wang, Guangmin Sun, Guangmin Sun, Xinming Zhang, Xinming Zhang, } "Handwritten character recognition based on hybrid neural networks", Proc. SPIE 4555, Neural Network and Distributed Processing, (20 September 2001); doi: 10.1117/12.441669; https://doi.org/10.1117/12.441669
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