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A defect detection system for PCB manufacturing system by applying the YOLOv4 algorithm

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Defect detection is recognized to be the most integral criterion for the printed circuit boards (PCBs) quality in industrial manufacturing. The traditional PCB inspection methods have several disadvantages such as time-consuming, labor-intensive, environmental clutter - susceptibility, and inaccurate detection ability. This paper offers a deep learning method for PCB defect detection. |

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