The Research of Printed Character Recognition Based on Neural Network

Yingqiao Shi, Wenbing Fan, Guodong Shi
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引用次数: 7

Abstract

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.
基于神经网络的印刷字符识别研究
本文首先介绍了人工神经网络技术在印刷字符识别中的应用现状,然后对标准BP神经网络技术进行了阐述。通过公式推导,指出标准BP神经网络在应用中存在一些缺陷,并采用加入动量项的方法对网络进行改进,提高了网络的训练速度。其次,我们随机选取200个印刷数字字符和50个印刷字母字符作为改进BP神经网络的样本进行实验,结果表明该方法对数字字符的识别率高于字母字符,收敛速度和识别性能都更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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