现代电子技术2017，Vol.40Issue(20)：111-113,3.DOI:10.16652/j.issn.1004-373x.2017.20.031
遗传算法优化神经网络在图像目标识别中的应用研究
Application of genetic algorithm optimizing neural network in image target recognition
摘要
Abstract
For the traditional target recognition methods are easy to fall into local optimum value and have low recognition accuracy,an image target recognition method based on genetic algorithm optimizing neural network is proposed. The texture ei-genvalues of the image are calculated by means of gray-level co-occurrence matrix(GLCM),and fused with the pixel grey-level value to form the feature vector of the classification image. The feature vector is input into neural network for training. The genet-ic algorithm adopted in neural network is used to get the best search range,and then the optimization operation is performed in high-order neural network to get the best image target recognition results. The experimental results show that the proposed meth-od has high superiority in the aspects of image target recognition accuracy and efficiency.关键词
遗传算法/特征矢量构成/神经网络/图像目标识别Key words
genetic algorithm/feature vector constitution/neural network/image target recognition分类
信息技术与安全科学引用本文复制引用
李隽,王伟..遗传算法优化神经网络在图像目标识别中的应用研究[J].现代电子技术,2017,40(20):111-113,3.基金项目
国家自然科学基金项目(61006027) （61006027）
