江汉大学学报（自然科学版）2016，Vol.44Issue(2)：131-136,6.DOI:10.16389/j.cnki.cn42-1737/n.2016.02.006
基于深度学习神经网络的SAR图像目标识别算法
SAR Images Target Recognition Algorithm Based on Deep Learning Neural Network
梁鑫 1徐慧1
作者信息
- 1. 南京林业大学 信息科学技术学院，江苏 南京 210037
- 折叠
摘要
Abstract
A new effective target recognition method for SAR images is proposed. First of all ,take the improved enhanced Lee filtering and HOG transformation for feature extraction of SAR images ,then through a hybrid neural network by cascading RBM and GRNN combination to operate object segmentation and target recognition of SAR images. Using MATLAB algorithm simulation of the test image database ,in this paper ,the method of object recognition based on the deep learning neural network algorithm can obviously increase the recognition rate ,and accuracy reaches 97%.关键词
目标识别/Lee滤波/HOG变换/深度学习/神经网络Key words
target recognition/Lee filtering/HOG transformation/deep learning/neural network分类
信息技术与安全科学引用本文复制引用
梁鑫,徐慧..基于深度学习神经网络的SAR图像目标识别算法[J].江汉大学学报（自然科学版）,2016,44(2):131-136,6.
