CKAN-YOLOv8: A Lightweight Multi-Task Network for Underwater Target Detection and Segmentation in Side-Scan Sonar
Underwater target detection and segmentation in Side-Scan Sonar (SSS) imagery is challenged by low signal-to-noise ratios, geometric distortions, and Unmanned Underwater Vehicles (UUVs)’ computational constraints. This paper proposes CKAN-YOLOv8, a lightweight multi-task network integrating Kolmogor...
Saved in:
| Main Authors: | Yao Xiao, Hualong Yang, Dongchen Dai, Hongjian Wang, Ziqi Shan, Hao Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/13/5/936 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SDA-Mask R-CNN: An Advanced Seabed Feature Extraction Network for UUV
by: Yao Xiao, et al.
Published: (2025-04-01) -
Recognition of Underwater Engineering Structures Using CNN Models and Data Expansion on Side-Scan Sonar Images
by: Xing Du, et al.
Published: (2025-02-01) -
Small object detection in side-scan sonar images based on SOCA-YOLO and image restoration
by: Xiaodong Cui, et al.
Published: (2025-04-01) -
Application and Analysis of the MFF-YOLOv7 Model in Underwater Sonar Image Target Detection
by: Kun Zheng, et al.
Published: (2024-12-01) -
Sharing Platform of Water Conservancy Data Based on CKAN
by: SONG Lili, et al.
Published: (2024-01-01)