机译:基于Sig-NMS的快速R-CNN组合转移学习用于VHR光学遥感影像中的小目标检测
Nanjing Univ Aeronaut & Astronaut Jiangsu Key Lab Internet Things & Control Technol Nanjing 211106 Jiangsu Peoples R China|Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Jiangsu Peoples R China|Jinling Inst Technol Nanjing 211169 Jiangsu Peoples R China;
Nanjing Univ Aeronaut & Astronaut Jiangsu Key Lab Internet Things & Control Technol Nanjing 211106 Jiangsu Peoples R China|Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 211106 Jiangsu Peoples R China;
Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ China Xian 710126 Shaanxi Peoples R China;
Shanghai Railway Adm Informat Technol Sect Jinhua 321000 Zhejiang Peoples R China;
Optical imaging; Optical sensors; Remote sensing; Object detection; Optical fiber networks; Task analysis; Deep convolution neural network; Faster R-CNN; non-maximum suppression (NMS); optical remote sensing images; Sig-NMS; small object detection; transfer learning;
机译:结合粗定位和分段分割技术改进VHR遥感影像中的建筑物变化检测
机译:通过改进的快速R-CNN在光学遥感图像中进行小目标检测
机译:通过深度传输学习的高分辨率光学遥感图像改变检测
机译:基于快速R-CNN的遥感影像精确目标检测
机译:用于遥感影像中目标检测和分类的无监督广义正交子空间投影和约束能量最小化。
机译:基于更快的R-CNN和高分辨率遥感图像的空间分析方法的烟囱检测
机译:基于对比度的VHR光学遥感图像的基于沉降性检测