DsPCBSD+

This dataset 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.

本数据集根据印刷电路板（Printed Circuit Board，简称PCB）表面缺陷的成因、位置及形貌等特征，将其划分为9个不同类别，并构建了PCB表面缺陷数据集（DsPCBSD+）。在DsPCBSD+数据集中，研究人员通过边界框对10259张图像中的20276处缺陷完成了手动标注。该开源可获取数据集旨在加速并推动基于深度学习（Deep Learning，简称DL）的PCB表面缺陷检测领域的相关研究与技术进步。