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Defect detection in steel surface is crucial for engineering quality control. Traditional methods for detecting surface defects on steel materials have issues such as low detection accuracy, slow speed, low level of intelligence, and insufficient utilization of images. In response to these challenges, this paper proposes an improved YOLOv8 model fo...
