An Application of CP Neural Network Based on Rough Set in Image Edge Detection

Min Dong, HuiYu Jiang, Xiangpeng Li, Qing Liu
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引用次数: 8

Abstract

Based on the rough set theory, a counter propagation neural network algorithm for edge detection is presented in this paper. Firstly, a definition of rough membership function, which is used to modify the weigh values in the nomal counter propagation neural network, is proposed after introducing the rough set. Experiments show that the approach has achieved good results in improving the accuracy of detection. And this algorithm can also overcome effectively the problem of simply cluster in the nomal counter propagation neural network.
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基于粗糙集的CP神经网络在图像边缘检测中的应用
基于粗糙集理论,提出了一种用于边缘检测的反传播神经网络算法。首先,在引入粗糙集的基础上,提出了粗糙隶属度函数的定义,用于修改普通反传播神经网络的权值;实验表明,该方法在提高检测精度方面取得了较好的效果。该算法还能有效地克服常规反传播神经网络的简单聚类问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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