Off-line handwritten Chinese character recognition based on GA optimization BP neural network

DOI

10.2991/icibet.2013.144How to use a DOI?

Abstract

For the shortcomings of traditional BP neural network, which are easy to fall into local extreme and slow convergence, but the genetic algorithm has the characteristics of global optimization. We combine the two to form an optimized BP neural network algorithm. This method combines the advantages of neural networks and genetic algorithms, which can effectively improve the recognition rate and recognition speed of off-line handwritten Chinese character.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huan Chen
AU  - Xiangnian Huang
AU  - Ping Cheng
AU  - Yan Xu
PY  - 2013/03
DA  - 2013/03
TI  - Off-line handwritten Chinese character recognition based on GA optimization BP neural network
BT  - Proceedings of the 2013 International Conference on Information, Business and Education Technology (ICIBET 2013)
PB  - Atlantis Press
SP  - 670
EP  - 673
SN  - 1951-6851
UR  - https://doi.org/10.2991/icibet.2013.144
DO  - 10.2991/icibet.2013.144
ID  - Chen2013/03
ER  -