机译:基于CNN的SAR图像分类的对抗性实例:体验研究
School of Geosciences and Info-Physics Central South University Changsha China;
School of Geosciences and Info-Physics Central South University Changsha China;
School of Geosciences and Info-Physics Central South University Changsha China;
School of Geosciences and Info-Physics Central South University Changsha China;
School of Geosciences and Info-Physics Central South University Changsha China;
School of Geosciences and Info-Physics Central South University Changsha China;
School of Geosciences and Info-Physics Central South University Changsha China;
School of Traffic and Transportation Engineering Central South University Changsha China;
Radar polarimetry; Target recognition; Remote sensing; Image recognition; Synthetic aperture radar; Radar imaging; Feature extraction;
机译:使用3D生成对抗网络进行偏振SAR图像分类
机译:通过深度卷积生成对抗网络解决SAR Imagery Ship分类不平衡
机译:SAR图像分类的分布与结构匹配生成对抗网络
机译:基于CNN图像取证的对抗性示例的可转移性
机译:关于对抗对抗例的分类问题
机译:二次操作的SAR图像生成并行连接对抗网络及其分类应用
机译:基于CNN的SAR图像分类的对抗性实例:体验研究