YOLOv5_4layers Based Small Target Defect Identification Method for PCB
Aiming at the issues such as low resolution,small target size,and diversity of surface defects for PCB,a PCB small target defect identification method based on YOLOv5_4layers was proposed.Based on the YOLOv5 architecture,a small target de-tection layer was added by adding a new sampling layer and optimizing the feature pyramid model with the purpose of improving the feature extraction performance of small targets and realizing the detection of smaller targets.After adjusting the appropriate an-chor frame specifications,the improved model has a 7.5%higher detection accuracy than the original model while the image input size is 640 pixels×640 pixels.When the image input size is 736 pixels×736 pixels,the accuracy rate is increased by 1.3%,which effectively improves the identification ability of PCB small target defects,and has practical significance for improving the quality control and product reliability of PCB manufacturing process.
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