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Physics-Guided Machine Learning for the Analysis of Low SNR STEM-EDXS Data

Published online by Cambridge University Press:  22 July 2022

Adrien Teurtrie ,
Nathanaël Perraudin ,
Thomas Holvoet ,
Hui Chen ,
Duncan T. L. Alexander ,
Guillaume Obozinski  and
Cécile Hébert
Adrien Teurtrie
Affiliation:
Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne Current address : Unité Matériaux et Transformations, UMET, UMR-CNRS 8207, Université de Lille, France
Nathanaël Perraudin
Affiliation:
Swiss Data Science Center, EPFL and ETH Zürich, Lausanne and Zürich
Thomas Holvoet
Affiliation:
Swiss Data Science Center, EPFL and ETH Zürich, Lausanne and Zürich Ghent University, Ghent
Hui Chen
Affiliation:
Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne
Duncan T. L. Alexander
Affiliation:
Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne
Guillaume Obozinski
Affiliation:
Swiss Data Science Center, EPFL and ETH Zürich, Lausanne and Zürich
Cécile Hébert*
Affiliation:
Electron Spectrometry and Microscopy Laboratory, Institute of Physics, EPFL, Lausanne
*
*Corresponding author: cecile.hebert@epfl.ch

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 2978 - 2979
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Copyright
Copyright © Microscopy Society of America 2022

References

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