\u300aA Review of Research on Steel Defect Detection Based on YOLO Series Algorithms\u300brelevant data

Name: \u300aA Review of Research on Steel Defect Detection Based on YOLO Series Algorithms\u300brelevant data
Creator: Sheng Zhang
Published: 2026-04-17T17:24:52+08:00

IEEE2026-04-17 收录

金属表面缺陷检测

工业视觉质量监控

数据链接：

https://ieee-dataport.org/documents/review-research-steel-defect-detection-based-yolo-series-algorithmsrelevant-data 数据链接链接失效反馈

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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

\u300aA Review of Research on Steel Defect Detection Based on YOLO Series Algorithms\u300brelevant data

资源简介：

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