YOLOv8-eRFD-AP: A Novel Domain Generalization Model for UAV-Based Insulator Inspection Under Adverse Weather Conditions
The deployment of artificial intelligence (AI)-powered uncrewed aerial vehicles (UAVs) for high-voltage power line inspection has become a crucial advancement in ensuring the stability and reliability of electrical transmission networks. Among various deep learning architectures, You Only Look Once...
Saved in:
| Main Authors: | Badr-Eddine Benelmostafa, Rita Aitelhaj, Hicham Medromi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11097281/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A systematic survey: role of deep learning-based image anomaly detection in industrial inspection contexts
by: Vinita Shukla, et al.
Published: (2025-06-01) -
Weather-Adaptive Synthetic Data Generation for Enhanced Power Line Inspection Using StarGAN
by: Blessing Agyei Kyem, et al.
Published: (2024-01-01) -
Improving Sewer Damage Inspection: Development of a Deep Learning Integration Concept for a Multi-Sensor System
by: Jan Thomas Jung, et al.
Published: (2024-12-01) -
Automated Visual Inspection for Precise Defect Detection and Classification in CBN Inserts
by: Li Zeng, et al.
Published: (2024-12-01) -
LARNet-SAP-YOLOv11: A Joint Model for Image Restoration and Corrosion Defect Detection of Transmission Line Fittings Under Multiple Adverse Weather Conditions
by: Yuxiang Gong, et al.
Published: (2025-01-01)