State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;
State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;
Remote sensing; Training; Agriculture; Scattering; Neural networks; Synthetic aperture radar; Veins;
机译:基于时间序列极化和光学数据的作物神经网络深层神经网络模型的比较研究
机译:野外流动捕获设备的作物疾病分类深度卷积神经网络
机译:POLSAR图像PIXELWISE分类的深模糊图卷积网络
机译:使用Polariemetric特征驱动的深卷积神经网络进行多时间POLSAR作物分类
机译:基于卷积神经网络和递归神经网络的深度神经语言文本分类模型
机译:基于融合的行星范围和Sentinel-2使用Incepion的融合的性能和Sentinel-2数据的性能启动深度卷积神经网络
机译:基于多时相遥感图像的三维卷积神经网络作物分类