Multi defect detection and analysis of electron microscopy images with deep learning

M Shen, G Li, D Wu, Y Liu, JRC Greaves, W Hao… - Computational Materials …, 2021 - Elsevier
Electron microscopy is widely used to explore defects in crystal structures, but human
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 …

[PDF][PDF] Multi Defect Detection and Analysis of Electron Microscopy

OT Sanchez, W Li, KG Field, D Morgan - academia.edu
Electron microscopy is widely used to explore defects in crystal structures, but human
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 …
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