Different algorithms for bearing defect detection performance. حسب Kangning Li (6069629)

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Algorithm detection performance. حسب Kangning Li (6069629)

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Defect detection results. حسب Guofeng Qin (11025170)

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Results of the bearing defect detection. حسب Kangning Li (6069629)

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Experimental data of ZFD-Net algorithm for defects. حسب Yang Gao (18005)

Comparison with other mainstream object detection algorithms. حسب Yang Gao (18005)

Target detection results (the detection results of proposed algorithm are on the left and YOLOv7 is on the middle YOLOv8-n is on the right). حسب Xiangqian Xu (17310895)

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Effect images of CLAHE algorithm. حسب Yang Gao (18005)

Performance of different algorithms. حسب Shiwei Yu (6060308)

Target detection results in different scenes (the detection results of proposed algorithm are on the left and YOLOv7 is on the middle YOLOv8-n is on the right). حسب Xiangqian Xu (17310895)

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Network structure diagram of YOLOv8 algorithm. حسب Weiyu Han (3448742)

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Network structure diagram of LMD-YOLO algorithm. حسب Weiyu Han (3448742)

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Detection results for short, spur, and spurious-copper defects. حسب Yazhou Li (277980)

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The defect images in the PCB defect dataset. حسب Shiwei Yu (6060308)

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Bearing defect dataset. حسب Kangning Li (6069629)

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Four types of surface defects. حسب Guofeng Qin (11025170)

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Performance of different algorithms. حسب Shiwei Yu (6060308)

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Algorithm detection steps. حسب José M. Rivera-Arbeláez (12418512)

An example of a labeled dataset with DB, TB, and DL tags representing three types of defects: Dot defect, stripe defect, and disconnection. حسب Hanfei Xie (18208462)

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Comparison table of filter algorithm parameters. حسب Xuanyi Zhao (5896112)

"…<div><p>In recent years, the demand for efficient and accurate defect detection algorithms in industrial production has been increasing. …"