Small defect detection in printed circuit boards based on the multiscale edge strengthening and an improved YOLOv10.

ABSTRACT: The manufacturing processes of Printed Circuit Boards (PCBs) have become increasingly complex, and even minor defects can significantly impair product performance and yield. Accurate identification of PCB defects is therefore crucial but remains challenging. Given the low resolution, small target size, and diverse nature of PCB surface defects, this study proposes a novel YOLO MSES-SPDConv (MS-YOLO) network based on an improved YOLOv10 framework to achieve more accurate and efficient detection of minor PCB defects with a smaller model size. Firstly, to address the performance bottleneck of the C2F module in the head network of YOLOv10 when processing complex PCB features, we introduce the Multiscale Edge Strengthening (MSES) structure to replace the traditional C2F module. The MSES structu

SUBMITTER: Chen W 

PROVIDER: S-EPMC12534475 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature