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Combining Character Level Classifier and Probabilistic Lexicons in Handwritten Word Recognition - Comparative Analysis of Methods

机译:组合字符级分类器和概率词汇在手写词识别中 - 方法对比分析

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In this paper the probabilistic aproach to handwritten words recognition is described. The decision is performed using results of character classification based on a character image analysis and probabilistic lexicon treated as a special kind of soft classifier. The novel approach to combining these both classifiers is proposed, where fusion procedure interleaves soft outcomes of both classifiers so as to obtain the best recog nition quality. The proposed algorithms were experimentally investigated and results of recognition of polish handwritten surnames and names are given.
机译:在本文中,描述了对手写单词识别的概率aproach。使用基于字符图像分析和概率词汇处理作为特殊类型的软分类器的概率分类来执行该决定。提出了组合这些两个分类器的新方法,其中融合过程交织了两个分类器的软结果,以获得最佳的认可金质量。提出的算法是通过实验研究的,并给出了策略的识别波兰手写姓氏和名称的结果。

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