Advancements in Steel Surface Defect Detection: An Enhanced YOLOv5 Algorithm with EfficientNet Integration
Fei Ren,
ZiAng Zhang,
Jiajie Fei
et al.
Abstract:Steel surface defect detection is of utmost importance for ensuring product quality, cost reduction, enhanced safety, and heightened customer satisfaction. To address the limitations of traditional steel surface defect detection algorithms, which often yielded singular detection results and suffered from high miss detection rates, we proposed an enhanced Yolov5 steel surface defect detection algorithm. In this approach, this paper employed the EfficientNet network as a replacement for the Yolov5 backbone netwo… Show more
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