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A multi-stage fuzzy classifier for off-line handwritten Chinese character recognition

机译:用于离线手写汉字识别的多级模糊分类器

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摘要

The decision boundaries in pattern recognition of large scale (PRLS) are usually complex and sometimes it is difficult to get ideal results with only a single classifier. In the paper, based on system integration idea, the method of fuzzy coarse classifying is given and a multi-stage fuzzy classifier is built. The recognition experiments on one level class of 3755 Chinese characters show that this method can largely improve the recognition accuracy. So it is an efficient method for solving PRLS.
机译:大规模模式识别(PRLS)的决策边界通常很复杂,有时仅使用一个分类器就很难获得理想的结果。本文基于系统集成思想,给出了模糊粗分类的方法,并建立了多级模糊分类器。对3755个汉字的一级分类进行的识别实验表明,该方法可以大大提高识别率。因此,它是解决PRLS的有效方法。

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