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Superior Neural Network for Distinguishing Between Atomic Species

Published online by Cambridge University Press:  30 July 2021

Matthew Helmi Leth Larsen ,
William Bang Lomholdt ,
Anders Siig Dreisig ,
Stig Helveg ,
Ole Winther ,
Thomas Hansen  and
Jakob Schiøtz
Matthew Helmi Leth Larsen
Affiliation:
Technical University of Denmark, United States
William Bang Lomholdt
Affiliation:
Technical University of Denmark, United States
Anders Siig Dreisig
Affiliation:
Technical University of Denmark, 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:
DTU Nanolab, Technical University of Denmark, Kgs. Lyngby, Hovedstaden, Denmark
Jakob Schiøtz
Affiliation:
Department of Physics, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark

Abstract

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Type
Full System and Workflow Automation for Enabling Big Data and Machine Learning in Electron Microscopy
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 466 - 468
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Madsen, Jacob, et al. “A Deep Learning Approach to Identify Local Structures in Atomic-Resolution Transmission Electron Microscopy Images.” Advanced Theory and Simulations, vol. 1, no. 8, Wiley-VCH Verlag, 2018, p. 1800037, doi:10.1002/adts.201800037.CrossRefGoogle Scholar
Ronneberger, Olaf, et al. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9351, Springer Verlag, 2015, pp. 234–41, doi:10.1007/978-3-319-24574-4_28.CrossRefGoogle Scholar
Pelt, Daniël M., and Sethian, James A. “A Mixed-Scale Dense Convolutional Neural Network for Image Analysis.” Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 2, National Academy of Sciences, 2018, pp. 254–59.CrossRefGoogle Scholar