Combining multiple classifiers based on statistical method for handwritten Chinese character recognition

Lei Lin, Xiaolong Wang, Bingquan Liu
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引用次数: 5

Abstract

In various application areas of pattern recognition, combining multiple classifiers is regarded as a method for achieving a substantial gain in performance of systems. The paper presents a method for handwritten Chinese character recognition to combine multiple classifiers based on statistics. Fusion strategies are discussed for providing a basis for combining classifiers. These combination strategies are experimentally tested on an online handwritten Chinese character recognition system. In our experiments, other combination approaches are also involved for comparison.
基于统计方法的多分类器组合手写体汉字识别
在模式识别的各个应用领域中,组合多个分类器被认为是实现系统性能大幅提高的一种方法。提出了一种基于统计的多分类器组合的手写体汉字识别方法。讨论了融合策略,为分类器的组合提供了基础。在一个在线手写体汉字识别系统上对这些组合策略进行了实验测试。在我们的实验中,还涉及了其他组合方法进行比较。
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