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Maximizing Neural Net Generalizability and Transfer Learning Success for Transmission Electron Microscopy Image Analysis in the Face of Small Experimental Datasets

Published online by Cambridge University Press:  22 July 2022

Katherine Sytwu ,
Luis Rangel DaCosta ,
Catherine Groschner  and
Mary C. Scott
Katherine Sytwu
Affiliation:
Molecular Foundry, Lawrence Berkeley National Lab, Berkeley, CA, USA
Luis Rangel DaCosta
Affiliation:
Molecular Foundry, Lawrence Berkeley National Lab, Berkeley, CA, USA Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, CA, USA
Catherine Groschner
Affiliation:
Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, CA, USA
Mary C. Scott*
Affiliation:
Molecular Foundry, Lawrence Berkeley National Lab, Berkeley, CA, USA Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, CA, USA
*
*Corresponding author: [email protected]

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. 3124 - 3126
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Copyright
Copyright © Microscopy Society of America 2022

References

Ruoqian, L et al. , Scientific reports 11(1) (2021): p. 1.Google Scholar
Manzorro, R et al. , Microscopy and Microanalysis 27(S1) (2021): p. 464.10.1017/S1431927621002154CrossRefGoogle Scholar
Khan, A et al. , Bulletin of the American Physical Society 65 (2020).Google Scholar
Groschner, CK, Choi, C and Scott, MC, Microscopy and Microanalysis 27(3) (2021): p. 549.10.1017/S1431927621000386CrossRefGoogle Scholar
Rangel DaCosta, L et al. , Micron 151 (2021): p. 103141.10.1016/j.micron.2021.103141CrossRefGoogle Scholar
Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.Google Scholar