Open access
2026
Ensemble-Based Self-Supervised Meta-Learning for Anomaly Detection in Power Systems
Experiments show that integrating meta-features and generated pseudo-labels achieves performance comparable to supervised learning based on the ground truth labels, demonstrating the proposed approach as a promising threshold independent solution for real-world, label-scarce industrial applications.
Sarala Mohan Naidu, Pawel Stano, J. Ottewill et al.
· IEEE Access · 0 citations