基于人工神经网络的多语言字符识别

S. Meiyappan, S. Sridharan, E. Ososanya
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引用次数: 1

摘要

字符识别是人工神经网络应用于处理的一个著名问题。但是,从多种语言中识别字符是相对较新的,需要深入研究。本文描述了一个这样的实现。设计了一个人工神经网络来识别泰米尔语和英语的双语字符集,即使在嘈杂的环境中也是如此。经过设计、实现、训练和测试,该系统对噪声字符的识别准确率达到93%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-lingual character recognition using artificial neural networks
Character recognition is one famous problem that artificial neural networks have been applied to deal with. But, recognizing characters from multiple languages is relatively new and needs to be investigated in depth. This paper describes one such implementation. An artificial neural network was designed to recognize a bilingual character set of Tamil and English, even in a noisy environment. The system was designed, implemented, trained and tested and was found to exhibit an accuracy of 93% on noisy characters.
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