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Reconstructing the exit wave in high-resolution transmission electron microscopy using machine learning

Published online by Cambridge University Press:  30 July 2021

Jakob Schiøtz
Affiliation:
Department of Physics, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark
Frederik Dahl
Affiliation:
Department of Physics, Technical University of Denmark, Hovedstaden, Denmark
Matthew Helmi Leth Larsen
Affiliation:
Department of Physics, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark
Christian Kisielowski
Affiliation:
Lawrene Berkeley National Laboratory, The Molecular Foundry and Joint center for Artifical Photosynthesis, University of California, Berkeley, United States
Stig Helveg
Affiliation:
Center for Visualizing Catalytic Processes (VISION), Department of Physics, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark., Kongens Lyngby, Hovedstaden, Denmark
Ole Winther
Affiliation:
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark
Thomas Hansen
Affiliation:
TU Nanolab, Technical University of Denmark, Kgs. Lyngby, Hovedstaden, Denmark
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Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Full System and Workflow Automation for Enabling Big Data and Machine Learning in Electron Microscopy
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

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Reconstructing the exit wave in high-resolution transmission electron microscopy using machine learning
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