Subtle Anomaly Detection of Microscopic Probes using Deep learning based Image Completion

Automated defect inspection in manufacturing of microscopic probes is an important task and often requires machine learning driven solutions. A supervised only approach can be challenging, because production manufacturing process typically have few defects, thus large amounts of labeled training data are generally not available. In this work, we instead employed multiple models in a multi-step process to achieve the end goal of identifying defect and non-defect probe tips.