NAVE	Networked Augmented Virtual Environment (NAVE) Group

Publication:Binyi Su, Zhong Zhou, Haiyong Chen. PVEL-AD: A Large-Scale Open-World Dataset for Photovoltaic Cell Anomaly Detection[J]. IEEE Transactions on Industrial Informatics (TII). 2023, 19(1):404-413. pdf (Top Journal, IF:11.648)         The anomaly detection in photovoltaic (PV) cell electroluminescence (EL) image is of great significance for the vision-based fault diagnosis. Many researchers are committed to solving this problem, but a large-scale open-world dataset is required to validate their novel ideas. We build a PV EL Anomaly Detection (PVEL-AD) dataset for polycrystalline solar cell, which contains 36,543 near-infrared images with various internal defects and heterogeneous background. This dataset contains anomaly-free images and anomalous images with 10 different categories. Moreover, 37,380 ground truth bounding boxes are provided for 8 types of defects. We also carry out a comprehensive evaluation of the state-of-the-art object detection methods based on deep learning. The evaluation results on this dataset provide the initial benchmark, which is convenient for follow-up researchers to conduct experimental comparisons. To the best of our knowledge, this is the first public dataset for PV solar cell anomaly detection that provides box-wise ground truth and focuses on industrial application. Furthermore, this dataset can also be used for the evaluation of many computer vision tasks such as few-shot detection, one-class classification and anomaly generation. create by admin at 2022-04-02 16:01:50