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Generic object detection algorithms for natural images have been proven to have excellent performance. In this paper, fabric defect detection on optical image datasets is systematically studied. In contrast to generic datasets, defect images are multi-scale, noise-filled, and blurred. Back-light intensity would also be sensitive for visual perception. Large-scale fabric defect datasets are collected, selected, and employed to fulfill the requirements of detection in industrial practice in orderdoi:10.3390/s20030871 pmid:32041348 pmcid:PMC7039386 fatcat:bw6ncpas5vcubjgejal2sfnera