AI RESEARCH
A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images
arXiv CS.AI
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ArXi:2605.19595v1 Announce Type: cross The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded insulation components. In recent years, Unmanned Aerial Vehicles (UAVs) combined with deep learning-based vision systems have emerged as an effective solution for automating this process. However, insulator fault detection remains challenging due to small defect regions, heterogeneous fault patterns, complex backgrounds, and varying imaging conditions.