Transformer enhanced based YOLOv8 integration: a hybrid deep learning framework for intelligent insulator defect detection in high-voltage transmission systems
Umer Farooq, Fan Yang, Jamshed Ali Shaikh · 2026
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Description
Umer Farooq, Fan Yang, and Jamshed Ali Shaikh present a hybrid detector for flaws in power line insulators, in work whose text is dated 2025. Missed defects in these parts can trigger major failures. Their system joins transformer attention with the YOLOv8 detector and adds modules for wide context, multi-scale fusion, and sharper box placement.
On two public datasets, the system scored near ninety-four percent on the standard detection measure, beating the plain YOLOv8 by about five points. It still ran in real time at more than eighty frames per second. Tests that remove one part at a time confirmed each module earns its place.
Catalog record
| CREATOR | Umer Farooq, Fan Yang, Jamshed Ali Shaikh |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 60 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |