FedRetinaNet is a federated learning-based object detection framework built on RetinaNet for insulator defect detection. It enables multiple clients to collaboratively train a high-performance detection model without sharing raw data, addressing data privacy challenges in power grid inspection systems. Optimized for detecting small-scale defects.
computer-vision pytorch deep-learning-algorithms object-detection smart-grid distributed-training privacy-preserving retinanet federated-learning defect-detection edge-ai small-object-detection power-grid ai-in-energy insulator-detection
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Updated
Apr 20, 2026 - Jupyter Notebook