期刊
OPTOELECTRONICS LETTERS
卷 13, 期 2, 页码 151-155出版社
TIANJIN UNIV TECHNOLOGY
DOI: 10.1007/s11801-017-7014-9
关键词
-
类别
资金
- National Natural Science Foundation of China [61401425]
In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independent of the ship target size is constructed by combining the shape feature with ship histogram of oriented gradient (S-HOG) feature, and the target can be recognized by AdaBoost classifier. As demonstrated in our experiments, the proposed method with the detection accuracy of over 96% outperforms the state-of-the-art method. efficiency switch and modulation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据