YOLO-HMC: An Improved Method for PCB Surface Defect Detection

The surface defects of printed circuit boards (PCBs) generated during the manufacturing process have an adverse effect on product quality, which further directly affects the stability and reliability of equipment performance. However, there are still great challenges in accurately recognizing tiny defects on the surface of PCB under the complex background due to its compact layout. To address the problem, a novel YOLO-HorNet-MCBAM-CARAFE (YOLO-HMC) network based on improved YOLOv5 framework is proposed in this article to identify the tiny-size PCB defect more accurately and efficiently with fewer model parameters. First, the backbone part adopts the HorNet for enhancing the feature extraction ability and…