Vision-Based Underwater Docking Guidance and Positioning: Enhancing Detection with YOLO-D
This study proposed a vision-based underwater vertical docking guidance and positioning method to address docking control challenges for human-operated vehicles (HOVs) and unmanned underwater vehicles (UUVs) under complex underwater visual conditions. A cascaded detection and positioning strategy in...
Saved in:
Main Authors: | Tian Ni, Can Sima, Wenzhong Zhang, Junlin Wang, Jia Guo, Lindan Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Journal of Marine Science and Engineering |
Subjects: | |
Online Access: | https://www.mdpi.com/2077-1312/13/1/102 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SCoralDet: Efficient real-time underwater soft coral detection with YOLO
by: Zhaoxuan Lu, et al.
Published: (2025-03-01) -
AquaYOLO: Enhancing YOLOv8 for Accurate Underwater Object Detection for Sonar Images
by: Yanyang Lu, et al.
Published: (2025-01-01) -
Advancing Underwater Vision: A Survey of Deep Learning Models for Underwater Object Recognition and Tracking
by: Mahmoud Elmezain, et al.
Published: (2025-01-01) -
Understanding the Influence of Image Enhancement on Underwater Object Detection: A Quantitative and Qualitative Study
by: Ashraf Saleem, et al.
Published: (2025-01-01) -
PGN: Progressively Guided Network with Pixel-Wise Attention for Underwater Image Enhancement
by: Huidi Jia, et al.
Published: (2025-01-01)