Structural diagram of the overall SCF-YOLO algorithm. by Yazhou Li (277980)

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PR curves of SCF-YOLO detection results. by Yazhou Li (277980)

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Confusion matrix of SCF-YOLO detection results. by Yazhou Li (277980)

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

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Detection results for missing hole, mouse bite, and open-circuit defects. by Yazhou Li (277980)

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Comparison of the semantic features of the C2f module and SCF module; (a) Semantic feature map for C2f Module; (b) Semantic feature map of the SCF module. by Yazhou Li (277980)

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(a): Sample statistical graphs of different types of defects. by Yazhou Li (277980)

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Diagram of 6 common types of PCB defect displays. by Yazhou Li (277980)

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Raw experimental data. by Yazhou Li (277980)

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Recall confidence curve. by Yazhou Li (277980)

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Dataset. by Yazhou Li (277980)

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Train process. by Yazhou Li (277980)

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Statistical chart of various loss changes during training. by Yazhou Li (277980)

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Schematic of Learnable weights fusion module. by Yazhou Li (277980)

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Data enhancement script. by Yazhou Li (277980)

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Original images. by Yazhou Li (277980)

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Structural diagram of the SCF module. by Yazhou Li (277980)

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Examples of unexpected situations in real applications. by Yazhou Li (277980)

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Configuration of training parameters. by Fangzhe Chang (20896737)

“…This method, named YOLOv5ds-RC, comprises three primary components: target detection, semantic segmentation, and edge optimization. …”

The principle of surface compression. by Fangzhe Chang (20896737)

“…This method, named YOLOv5ds-RC, comprises three primary components: target detection, semantic segmentation, and edge optimization. …”