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Large-scale Automated Analysis of High-Resolution Transmission Electron Microscopy Data Assisted by Deep Learning Neural Networks

Published online by Cambridge University Press:  22 July 2022

Matthew Helmi Leth Larsen*
Affiliation:
DTU Physics, Technical University of Denmark, Kgs. Lyngby, Denmark
Cuauhtémoc Nuñez Valencia
Affiliation:
DTU Physics, Technical University of Denmark, Kgs. Lyngby, Denmark
William Bang Lomholdt
Affiliation:
DTU Nanolab, Technical University of Denmark, Kgs. Lyngby, Denmark
Daniel Kelly
Affiliation:
DTU Nanolab, Technical University of Denmark, Kgs. Lyngby, Denmark
Pei Liu
Affiliation:
DTU Nanolab, Technical University of Denmark, Kgs. Lyngby, Denmark
Jakob Birkedal Wagner
Affiliation:
DTU Nanolab, Technical University of Denmark, Kgs. Lyngby, Denmark
Ole Winther
Affiliation:
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark
Thomas Willum Hansen
Affiliation:
DTU Nanolab, Technical University of Denmark, Kgs. Lyngby, Denmark
Jakob Schiøtz
Affiliation:
DTU Physics, Technical University of Denmark, Kgs. Lyngby, Denmark
*
*Corresponding author: [email protected]

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Copyright
Copyright © Microscopy Society of America 2022

References

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Pelt, DM and Sethian, JA, PNAS of the United States of America 115 (2018), p. 254. doi: 10.1073/pnas.1715832114Google Scholar