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Handwritten Digits Recognition Using HMM and PSO based on storks

机译:使用HMM和PSO的手写的数字识别基于鹳

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A new method for handwritten digits recognition based on hidden markov model (HMM) and particle swarm optimization (PSO) is proposed. This method defined 24 strokes with the sense of directional, to make up for the shortage that is sensitive in choice of stating point in traditional methods, but also reduce the ambiguity caused by shakes. Make use of excellent global convergence of PSO; improving the probability of finding the optimum and avoiding local infinitesimal obviously. Experimental results demonstrate that compared with the traditional methods, the proposed method can make most of the recognition rate of handwritten digits improved.
机译:提出了一种基于隐马尔可夫模型(HMM)和粒子群优化(PSO)的手写数字识别的新方法。该方法定义了具有定向感的24冲程,弥补了在传统方法中选择说明点的缺点,但也减少了由奶昔引起的歧义。利用PSO的优秀全球收敛;显然提高找到最佳和避免局部无限的概率。实验结果表明,与传统方法相比,所提出的方法可以使大部分手写数字的识别率改善。

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