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Handwritten Character Recognition Based on BP Neural Network

机译:基于BP神经网络的手写字符识别

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This paper researches on the issue of computer recognition to the handwritten character images, including lowercase letters and Arabic numerals. In this paper, we preprocess on characters in order to unified the basic features. And then, we apply the basic method of making the grids to extract the features of chacrater, and classify the respectives. At last, we apply the latest heuristic modifications of Back propagation algorithm to recognize the handwritten characters successfully. The basic datas of this research are testing and debugging on visual studio 2005, a large number of test experiments' datas show that the discrimination of heuristic modifications of Back propagation algorithm is up to 95 percentage, further improving validity and correctness of this latest algorithm.
机译:本文研究了计算机识别对手写字符图像的问题,包括小写字母和阿拉伯数字。在本文中,我们预处理字符才能统一基本功能。然后,我们应用制作网格的基本方法,以提取Chacrater的特征,并对各自进行分类。最后,我们应用了后传播算法的最新启发式修改,以识别成功的手写字符。本研究的基本数据数据正在Visual Studio 2005上进行测试和调试,大量的测试实验数据显示后传播算法的启发式修改的判断高达95个百分点,进一步提高了该算法的有效性和正确性。

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