Surface defect detection of steel based on improved YOLOv5 algorithm

To address the challenge of achieving a balance between efficiency and performance in steel surface defect detection, this paper presents a novel algorithm that enhances the YOLOv5 defect detection model. The enhancement process begins by employing the K-means++ algorithm to fine-tune the location o...

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Bibliographic Details
Published in:	Mathematical Biosciences and Engineering
Main Author:	Yiwen Jiang
Format:	Article
Language:	English
Published:	AIMS Press 2023-11-01
Subjects:	defect detection yolov5 se-net eiou carafe upsampling
Online Access:	https://www.aimspress.com/article/doi/10.3934/mbe.2023879?viewType=HTML

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