Off-line handwritten Chinese character recognition based on GA optimization BP neural network
- 10.2991/icibet.2013.144How to use a DOI?
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.
- © 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/).
Cite this article
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 -