[1]万琴,李智,李伊康,等.基于改进YOLOX的移动机器人目标跟随方法[J/OL].自动化学报:1-15(2023-01-06)[2023-01-28].https://doi.org:10.16383/j.aas.c220344. [2]郭敬东.改进的YOLOX输电线路环境及部件异常分级检测[J].电力信息与通信技术,2022,20(11):27-36. [3]刘健. 基于YOLOX的输电线路异物检测算法研究及软件设计[D].徐州:中国矿业大学,2022. [4]王素珍,赵霖,邵明伟,等.基于改进YOLOv5的输电线路绝缘子识别方法[J].电子测量技术,2022,45(21):181-188. [5]武建超,张楠,闫彦辉,等.基于改进YOLOv4-tiny的输电线路目标识别算法[J].测控技术,2022,41(11):28-34. [6]戴永东,蒋中军,王茂飞,等.基于深度学习的输电线路均压环倾斜识别[J].自动化仪表,2022,43(9):106-110. [7]陈远. 基于超声波传感的障碍物检测和测距系统设计[D].成都:电子科技大学,2019. [8]雷艳敏,朱齐丹,仲训昱,等.基于激光测距仪的障碍物检测的仿真研究[J].计算机工程与设计,2012,33(2):718-723. [9]王泽民,高俊钗.单目视觉障碍物测距精度分析[J].电子测试,2016(18):36-37. [10]李家俊. 基于改进YOLOX的目标检测与跟踪算法研究[D].赣州:江西理工大学,2022. [11]Wang Linlin,Li Junjie,Kang Fei. Crack Location and Degree Detection Method Based on YOLOX Model[J]. Applied Sciences, 2022, 12(24) : 12572. [12]Kefu Yi,Kai Luo,Tuo Chen,et al. An Improved YOLOX Model and Domain Transfer Strategy for Nighttime Pedestrian and Vehicle Detection[J]. Applied Sciences, 2022, 12(23) : 12476. [13]Peng Gao,Kangbeen Lee,Lukas Wiku Kuswidiyanto, et al. Dynamic Beehive Detection and Tracking System Based on YOLO V5 and Unmanned Aerial Vehicle[J]. Journal of Biosystems Engineering, 2022, 47(4) : 510-520. [14]Lei Zhang,Shangkai Hao,Haosheng Wang, et al. Safety Warning of Mine Conveyor Belt Based on Binocular Vision[J]. Sustainability, 2022, 14(20) : 13276. [15]Xuguang Yuan,Dan Li,Peng Sun,et al. Real-Time Counting and Height Measurement of Nursery Seedlings Based on Ghostnet–YoloV4 Network and Binocular Vision Technology[J]. Forests, 2022, 13(9) : 1459. [16]周仲波,简蓓,田地,等.基于双目视觉的智能变电站巡检路径规划方法[J].电气技术与经济,2022(6):79-81,96. [17]汪凌阳,朱璠婷,蒋文萍.基于机器视觉的机械臂双目测距系统研究[J].应用技术学报,2022,22(4):383-387. [18]闫德鑫,刘建军.无人机双目视觉系统在电力绝缘子故障检测与类型识别中的研究与应用[J].佳木斯大学学报(自然科学版),2022,40(6):128-133. [19]Jian Xu,Jinbin Li,Xin Chen,et al. A High-Precision Power Line Recognition and Location Method Based on Structured-Light Binocular Vision[J]. Journal of Advanced Computational Intelligent Informatics, 2022, 26(5) : 691-697. [20]王迪迪,候嘉豪,王富全,等.基于双目视觉的目标检测与测距研究[J].电子制作,2022,30(21):58-61. |