DsPCBSD+

This work categorized PCB surface defects into 9 distinct categories based on factors such as their causes, locations, and morphologies and developed a dataset of PCB surface defect (DsPCBSD+). In DsPCBSD+, a total of 20,276 defects were annotated manually by bounding boxes on the 10,259 images. This openly accessible dataset is aimed accelerating and promoting further researches and advancements in the field of DL-based detection of PCB surface defect.

本研究依据缺陷成因、出现位置与形貌特征等因素，将印刷电路板（Printed Circuit Board，PCB）表面缺陷划分为9个不同类别，并构建了PCB表面缺陷数据集（DsPCBSD+）。该数据集包含10259张图像，其中20276处缺陷均通过边界框完成人工标注。作为一款公开可获取的数据集，其旨在加速并推动基于深度学习（Deep Learning，DL）的PCB表面缺陷检测领域的相关研究与技术进步。