AquaYOLO: Advanced YOLO-based fish detection for optimized aquaculture pond monitoring
Abstract Aquaculture plays an important role in ensuring global food security, supporting economic growth, and protecting natural resources. However, traditional methods of monitoring aquatic environments are time-consuming and labor-intensive. To address this, there is growing interest in using com...
Saved in:
| Main Authors: | M. Vijayalakshmi, A. Sasithradevi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-89611-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
BGLE-YOLO: A Lightweight Model for Underwater Bio-Detection
by: Hua Zhao, et al.
Published: (2025-03-01) -
VBM-YOLO: an enhanced YOLO model with reduced information loss for vehicle body markers detection
by: Bin Wang, et al.
Published: (2025-06-01) -
HFC-YOLO11: A Lightweight Model for the Accurate Recognition of Tiny Remote Sensing Targets
by: Jinyin Bai, et al.
Published: (2025-05-01) -
YOLO-PWSL-Enhanced Robotic Fish: An Integrated Object Detection System for Underwater Monitoring
by: Lingrui Lei, et al.
Published: (2025-06-01) -
FF-YOLO: An Improved YOLO11-Based Fatigue Detection Algorithm for Air Traffic Controllers
by: Shijie Tan, et al.
Published: (2025-07-01)