Solar Panel Fault Detection Using Deep Learning: A Computer Vision Approach This project presents an automated system for detecting and classifying faults in solar panels using state-of-the-art deep learning and computer vision techniques. Leveraging an EfficientNetB0-based architecture, the model accurately identifies six categories of faults: bi
docker computer-vision deep-learning tensorflow solar-panels fault-detection predictive-maintenance real-time-detection fastapi sustainable-energy efficieantnetb0
-
Updated
Apr 24, 2025 - PureBasic