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Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Engineering and Technology

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Y. Guo, S. V. Kalinin, et al.

Explore groundbreaking research by Yueming Guo and colleagues as they unveil a novel unsupervised machine learning technique for defect detection in complex materials using scanning transmission electron microscopy. This method leverages one-class support vector machines to classify defects, eliminating the need for human-labeled data.... show more
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27
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43
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Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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