Abstract:
Automated defect inspection in manufacturing of microscopic probes is an important task and often requires machine learning driven solutions. A supervised only approach c...Show MoreMetadata
Abstract:
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.
Published in: 2019 IEEE International Test Conference (ITC)
Date of Conference: 09-15 November 2019
Date Added to IEEE Xplore: 17 February 2020
ISBN Information: