基于BP神经网络的字符识别研究

2011 Second International Conference on Mechanic Automation and Control Engineering Pub Date : 2011-07-15 DOI:10.1109/MACE.2011.5988090

Pingchang Zhu, Kai Xu, Chunmei Wang, Hong Ye, F. Wang, Hui-ting Zhao

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引用次数: 0

摘要

本文研究了将EMD与非线性主成分分析相结合，提取汽车品牌特征识别的方法。其主要思想是在预先加入动量因子的BP神经网络中对目标图像进行识别，其中包含字符识别技术。之后与改进后的神经网络在不同参数场合的性能进行了比较，实验证明该方法可以提高字符识别神经网络的训练速度和精度。

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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Character recognition research based on BP neural network

This article is about the method on how to extract character recognition of vehicle brand by the combinition of EMD and nonlineary PCA. The main idea is to identify the image of the object which contains character recognition technology in BP neural network that momentum factor has been added in advance. After that compared with the improved neural network performance in different parameter occasions, the test proved that this method can increase the training speed and precision of character Recognition neural network.

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来源期刊

2011 Second International Conference on Mechanic Automation and Control Engineering

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