机译:基于UAV的衔接式支持设备检查的提高R-CNN
State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Haidian District Beijing 100044 P. R. China School of Traffic and Transportation Beijing Jiaotong University Haidian District Beijing 100044 People's Republic of China;
State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Haidian District Beijing 100044 P. R. China School of Traffic and Transportation Beijing Jiaotong University Haidian District Beijing 100044 People's Republic of China;
State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Haidian District Beijing 100044 P. R. China School of Traffic and Transportation Beijing Jiaotong University Haidian District Beijing 100044 People's Republic of China;
State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Haidian District Beijing 100044 P. R. China School of Traffic and Transportation Beijing Jiaotong University Haidian District Beijing 100044 People's Republic of China;
State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Haidian District Beijing 100044 P. R. China School of Traffic and Transportation Beijing Jiaotong University Haidian District Beijing 100044 People's Republic of China;
State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Haidian District Beijing 100044 P. R. China School of Traffic and Transportation Beijing Jiaotong University Haidian District Beijing 100044 People's Republic of China;
Catenary support device; improved Faster R-CNN; UAV image; fasteners; automatic defect detection;
机译:云边缘计算环境中使用更快的R-CNN的智能表面检测系统
机译:基于改进的R-CNN的移动机械手快速检测和GraspingMethod
机译:提高快速车辆检测的速度框架框架
机译:使用改进的快速R-CNN检测悬链支撑装置上防鸟和紧固件的缺陷
机译:用于检测MR兼容导管的更快R-CNN模型
机译:基于更快的R-CNN的改进算法肺炎检测
机译:使用深卷积神经网络自动缺损紧固件上紧固件的缺陷检测