detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable
to large numbers of images or real-time analysis. In this work, we discuss the application of
machine learning approaches to find the location and geometry of different defect clusters in
irradiated steels. We show that a deep learning based Faster R-CNN analysis system has a
performance comparable to human analysis with relatively small training data sets. This …