Research on Collaborative Object Detection and Recognition of Autonomous Underwater Vehicle Based on YOLO Algorithm
文献类型：会议论文
| 作者 | Tang LS(唐磊生)1,4; Xu HL(徐红丽)2 ; Wu H(吴函)1; Tan DX(谭东旭)3; Gao L(高雷)1
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| 出版日期 | 2021 |
| 会议日期 | May 22-24, 2021 |
| 会议地点 | Kunming, China |
| 关键词 | Underwater Vehicle YOLO Neural Network Real-time Detection Target Recognition |
| 页码 | 1664-1669 |
| 英文摘要 | Autonomous underwater vehicle (AUV) is an important tool for human to explore and research marine resources. Due to the influence of underwater environment, it is impossible to realize the rapid detection and recognition of AUV and the recognition of cooperative objects. To solve this problem, underwater light vision and underwater image enhancement technology are proposed to realize the rapid detection and recognition of underwater vehicles, so as to realize the recognition of cooperative objects. In this paper, YOLO algorithm which has a good effect on target detection precision and the recognition speed is used to recognize the underwater vehicle on the Yolo network. For the original data set, histogram equalization and CLAHE algorithm are used to enhance the image. They are respectively loaded into the same training model and trained on the yolov2 and yolov3 networks. The analysis of the experimental results shows that the underwater image enhancement technology based on the YOLOv3 network and the CLAHE algorithm can meet the requirements of rapid recognition for underwater vehicle detection and recognition. |
| 产权排序 | 1 |
| 会议录 | 2021 33rd Chinese Control and Decision Conference (CCDC)
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISSN号 | 1948-9447 |
| ISBN号 | 978-1-6654-4089-9 |
| 源URL | [http://ir.sia.cn/handle/173321/29956]  |
| 专题 | 沈阳自动化研究所_海洋信息技术装备中心 |
| 通讯作者 | Tang LS(唐磊生) |
| 作者单位 | 1.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China 2.Northeastern University, Shenyang, China 3.School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, China 4.Information & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Tang LS,Xu HL,Wu H,et al. Research on Collaborative Object Detection and Recognition of Autonomous Underwater Vehicle Based on YOLO Algorithm[C]. 见:. Kunming, China. May 22-24, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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