EGRN-YOLO: An Enhanced Multi-View Remote Sensing Detection Algorithm for Onshore Wind Turbines Based on YOLOv7
Wind turbines, as the core components of wind power generation systems, play a crucial role in determining the overall generation efficiency and operational safety. However, the challenges posed by complex backgrounds, significant variations in the scale of wind turbine targets, and arbitrary orient...
Saved in:
| Main Authors: | Renzheng Xue, Haiqiang Xu, Qianlong Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10910190/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Surface Defect Detection Algorithm for Wind Turbine Blades Based on HSCA-YOLOv7
by: Bing LI, et al.
Published: (2023-08-01) -
YOLO-WTB: Improved YOLOv12n Model for Detecting Small Damage of Wind Turbine Blades From Aerial Imagery
by: Phat T. Nguyen, et al.
Published: (2025-01-01) -
Enhancing wind turbine blade damage detection with YOLO-Wind
by: Zhao Zhanfang, et al.
Published: (2025-05-01) -
GCB‐YOLO: A Lightweight Algorithm for Wind Turbine Blade Defect Detection
by: Zhiming Zhang, et al.
Published: (2025-06-01) -
A novel edge crop method and enhanced YOLOv5 for efficient wind turbine blade damage detection
by: Boyu Feng, et al.
Published: (2025-07-01)