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.
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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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