A multi-perspective deep learning approach for optical inspection of crimp connections

In the era of digitalization and big data, the evolution of electrical systems and their manufacturing is closely tied to the advancement of machine learning, particularly in the industrial sector. With the rise of electromobility and constant connectivity, there is a growing demand for efficient signal and power networking, where the crimp connection plays a critical role. Against this background, this study introduces an intelligent computer vision pipeline that leverages multiperspective deep learning models for automated and comprehensive quality inspection of crimp connections.