文章基本信息

标题：A Selection Algorithm of Training Set Based on Similar Classification
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作者：Liang, Xiaowen ; Gong, Wei ; Fu, Wenlong 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2014
卷号：9
期号：3
页码：726-731
DOI：10.4304/jsw.9.3.726-731
语种：English
出版社：Academy Publisher
摘要：License Plate Recognition (LPR) combines computer vision technology andpattern recognition technology and plays an important role in Freeway TollSystem, Urban Road Monitoring System and the Intelligent Parking Lot ManagementSystem. Therefore, it has attracted an ever increasing number of scholars fromhome and abroad. Despite many years of unremitting effort which has resulted inbreakthrough achievements, it remains unsatisfactory in meeting real worldapplication requirements. LPR primarily employs pattern recognition and digitalimage process technology. This paper is focused on the study of patternrecognition. The segmented characters are trained utilizing the BP neuralnetwork. Selecting the ideal training set from the usually large sample set wehave is the first step to train a good network which has a high recognitionrate. At present, training sets are randomly selected, which affects theaccuracy of recognition as well as its speed. Thus, selecting the best trainingsets is of uttermost importance. In this paper, Similarity Comparison Samplingmethod is proposed to improve the training results.
关键词：training set; selection algorithm; neural network; character recognition