\u300aA Review of Research on Steel Defect Detection Based on YOLO Series Algorithms\u300brelevant data
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https://ieee-dataport.org/documents/review-research-steel-defect-detection-based-yolo-series-algorithmsrelevant-data
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资源简介：
The GC10-DET dataset is available on github (https:\/\/github.com\/lvxiaoming2019\/GC10-DET-Metallic-Surface-Defect-Matasets)GC10-DET is a dataset of surface defects collected in a real industry. A real industry. It contains ten types of surface defects, namely punches (Pu), welds (Wl), crescent gaps (Cg), water spots (Water Spot). (Cg), water spots (Ws), oil spots (Os), silk spots (Ss), inclusions (In), rolling pits (Rp), creases (Cr), waist creases (Wf). The collected defects are all on the surface of steel plates. The dataset includes 3570 grey release images
提供机构：
Sheng Zhang
