The Research of Printed Character Recognition Based on Neural Network - Yingqiao Shi; Wenbing Fan; Guodong Shi (2011 Fourth International Symposium on Parallel Architectures, Algorithms and Programming, 2011)
Firstly, This paper introduces the application status of the artificial neural network technology in the print character recognition, and then elaborated on the technology of Standard BP neural network. By formula derivation, we showed that Standard BP neural Network exists some defects in the application, and then we take the approach by adding a momentum term to improve the Network, and increases the training speed. Secondly, we randomly selecte 200 printed number-characters and 50 printed letter-characters as a sample of the improved BP neural network experiments, the results show that the method of the number-character recognition rate higher than the alphabetic characters, the performance of convergence speed and recognition is better.