一种深度神经网络SAR图像目标识别可视化方法

A visualization method for SAR image target recognition by deep neural network

针对深度神经网络模型判别模型构建依据不清晰的问题,提出一种基于特征缺损的雷达SAR图像目标识别分析方法.该方法移除目标图像的局部特征信息,并将其作为输入样本,获取深度神经网络识别结果的变化关系,根据深度神经网络模型分类输出结果的变化情况,分析深度神经网络实现目标分类的原理.在公开的MSTAR数据集上的实验表明,该方法可以有效展现目标不同区域的信息对深度网络识别的影响,实现深度神经网络识别的可视化分析.

Aiming at the problem that the construction basis of discriminant model of deep neural network(DNN)model is not clear,this paper proposes a feature defect-based method of radar SAR image target recognition and analysis.The paper uses the method to remove the local feature information of the target image,takes it as the input sample to obtain the variation relation of the recognition result of the DNN,and finally accords to the DNN model to classify the variation of the output results,analyzing the principle of DNN achieving target classification.Experiments conducted on publicly available MSTAR datasets show that the proposed method can effectively present the influence of different regions of the target information on deep network recognition,and realize the visualization analysis of DNN recognition.