Advancing Automatic Photovoltaic Defect Detection using Semi-Supervised Semantic Segmentation of Electroluminescence Images
A semi-supervised deep learning framework, PV-S3, that efficiently utilizes both labeled and unlabeled electroluminescence images to accurately detect and segment various types of photovoltaic cell defects.
