文章基本信息

标题：A Neural Network Based Character Recognition System Using Double Backpropagation
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作者：Joarder Kamruzzaman ; S. M. Aziz
期刊名称：Malaysian Journal of Computer Science
印刷版ISSN：0127-9084
出版年度：1998
卷号：11
期号：1
出版社：University of Malaya * Faculty of Computer Science and Information Technology
摘要：Proposes a neural network based invariant character recognition system using double backpropagation network. The model consists of two parts. The first is a preprocessor which is intended to produce a translation, rotation and scale invariant representation of the input pattern. The second is a neural net classifier. The outputs produced by the preprocessor at the first stage are classified by this neural net classifier trained by a learning algorithm called double backpropagation. The recognition system was tested with ten numeric digits (0~9). The test included rotated, scaled and translated version of exemplar patterns. This simple recognizer with double backpropagation classifier could successfully recognize nearly 97% of the test patterns.
关键词：Neural networks; backpropagation; double backpropagation; character recognition; Rapid Transform