YOLO-DBS: Efficient Target Detection in Complex Underwater Scene Images Based on Improved YOLOv8
Chinese Academy of Sciences · Changchun Institute of Optics, Fine Mechanics and Physics · +1 more institution
Indexed incrossref
Abstract
No abstract available for this paper.
Citation impact
47
total citations
- FWCI
- 47.43
- Percentile
- 100%
- References
- 50
Citations per year
Authors
4- XWXinhua WangCorresponding
Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics, Northeast Electric Power University
- XSXiangyang Song
Northeast Electric Power University
- ZLZhuang Li
Northeast Electric Power University
- HWHeqi Wang
Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics
Topics & keywords
Topics
Keywords
- Underwater
- Computer vision
- Artificial intelligence
- Computer science
- Environmental science
- Remote sensing
- Geology
- Oceanography
UN Sustainable Development Goals
- Life below water
No related works found for this paper.