计算机科学
分类器(UML)
人工神经网络
稳健性(进化)
人工智能
字符识别
模式识别(心理学)
反向传播
边缘分级机
时滞神经网络
语音识别
生物化学
基因
图像(数学)
化学
作者
Fuliang Li,Shuangxi Gao
标识
DOI:10.1109/mvhi.2010.185
摘要
According to the characteristics of vehicle license plate, recognition algorithm was proposed based on back-propagation (BP) neural network. Classifier was divided into Chinese characters classifier, English letters classifier, English letters and numbers mixed classifier, and digital classifier these four kinds of classifier in the algorithm. This neural network design can effectively simplify the network structure, improved recognition accuracy and speed. BP algorithm went along improvement as the defects of the standard BP algorithm which had slow convergence and easy to fall into local minimum points. Through simulation experiments, the character recognition system not only has a higher recognition rate, but also has better neural network robustness to decrease failures, that is having good robustness characteristics.
科研通智能强力驱动
Strongly Powered by AbleSci AI