Motion Behavior Recognition of Underwater Vehicle Based on YOLOv3

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 海洋信息技术装备中心

	Motion Behavior Recognition of Underwater Vehicle Based on YOLOv3
	Tang LS(唐磊生)3,4; Hou, Jing 4; Xu HL(徐红丽)2; Wu MY(吴梦妍)3; Xia, Xinyang 5; Cui, Yifan 1
	2020
会议日期	October 28-30, 2020
会议地点	Xi'an, Virtual, China
关键词	YOLOv3 Neural Networks Underwater Vehicle Detection Target Recognition
页码	1-6
英文摘要	As an important tool for human exploration and understanding of the ocean, underwater vehicle cannot achieve real-time cooperation due to the limitations of underwater acoustic communication. In order to realize the recognition and perception of the cooperative object behavior of underwater vehicle by vision, a new method is provided for the cooperation between underwater vehicle. Select YOLOv3 target detection algorithm, this paper to test the underwater vehicle motion behavior recognition, first of all, the collected experimental data set, using Label Image software training set and testing set of calibration, and modify the YOLOv3 classifier, change the output of the network dimension, optimization of network parameters and accelerate the convergence of the model, by analysing the experimental result shows that using YOLOv3 network, can realize the four directions to set an underwater vehicle motion behavior recognition, and ensure the accuracy and speed, the foundation for subsequent underwater vehicle based on visual collaboration.
产权排序	1
会议录	2020 International Conference on Mechanical Automation and Computer Engineering, MACE 2020 - Mechanical Automation
会议录出版者	IOP Publishing Ltd
会议录出版地	Bristol, UK
语种	英语
ISSN号	1742-6588
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/28489]
专题	沈阳自动化研究所_海洋信息技术装备中心
通讯作者	Hou, Jing
作者单位	1.Hai Nan University, Hai Kou, China 2.Northeastern University, Liaoning, China 3.Shenyang Institute of Automation Chinese Academy of Science, Liaoning, China 4.Shenyang Jianzhu University, Liaoning, China 5.Shenyang University of Technology, Liaoning, China
推荐引用方式 GB/T 7714	Tang LS,Hou, Jing,Xu HL,et al. Motion Behavior Recognition of Underwater Vehicle Based on YOLOv3[C]. 见:. Xi'an, Virtual, China. October 28-30, 2020.