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A new combination scheme for HMM-based classifiers and its application to handwriting recognition

机译:基于HMM的分类器的一种新组合方案及其在手写识别中的应用。

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Handwritten text recognition is one of the most difficult problems in the field of pattern recognition. The combination of multiple classifiers has been proven to be able to increase the recognition rate when compared to single classifiers. In this paper a new combination method for HMM based handwritten word recognizers is introduced. In contrast with many other multiple classifier combination schemes, where the combination takes place at the decision level, the proposed method combines various HMMs at a more elementary level. The usefulness of the new method is experimentally demonstrated in the context of a handwritten word recognition task.
机译:手写文本识别是模式识别领域中最困难的问题之一。与单个分类器相比,多个分类器的组合已被证明能够提高识别率。本文介绍了一种新的基于HMM的手写单词识别器组合方法。与许多其他多分类器组合方案(决策在组合级别上进行)形成对比,所提出的方法在更基本的层次上组合了各种HMM。在手写单词识别任务的背景下,通过实验证明了该新方法的实用性。

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