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Morphological self-organizing feature map neural network with applications to automatic target recognition
Zhang SJ(张世俊) ; Jing ZL(敬忠良) ; Li JX(李建勋)
刊名http://epub.edu.cnki.net/grid2008/brief/detailj.aspx?filename=GXKB200501005&dbname=CJFQ2005
2012-04-24 ; 2012-04-24
关键词李建勋
中文摘要<正>The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.
语种中文
其他责任者Institute of Aerospace Information and Control School of Electronic Information and Electrical Engineering ; Shanghai Jiao Tong University ; Shanghai 200030
内容类型期刊论文
源URL[http://ir.calis.edu.cn/hdl/231030/1574]  
专题上海交通大学
推荐引用方式
GB/T 7714
Zhang SJ,Jing ZL,Li JX. Morphological self-organizing feature map neural network with applications to automatic target recognition[J]. http://epub.edu.cnki.net/grid2008/brief/detailj.aspx?filename=GXKB200501005&dbname=CJFQ2005,2012, 2012.
APA 张世俊,敬忠良,&李建勋.(2012).Morphological self-organizing feature map neural network with applications to automatic target recognition.http://epub.edu.cnki.net/grid2008/brief/detailj.aspx?filename=GXKB200501005&dbname=CJFQ2005.
MLA 张世俊,et al."Morphological self-organizing feature map neural network with applications to automatic target recognition".http://epub.edu.cnki.net/grid2008/brief/detailj.aspx?filename=GXKB200501005&dbname=CJFQ2005 (2012).
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