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Convolutional Neural Network as a Solution to Segment and Classify High Resolution TEM Images to Obtain 3D Information

Published online by Cambridge University Press:  22 July 2022

M. Leibovich ,
R. Manzorro ,
Mai Tan ,
S. Mohan ,
Adrià Marcos-Morales ,
C. Fernandez-Granda  and
P. A. Crozier
M. Leibovich
Affiliation:
Courant Institute of Mathematical Sciences and Center for Data Science, New York University, New York, NY, United States
R. Manzorro
Affiliation:
School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, Arizona, United States
Mai Tan
Affiliation:
School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, Arizona, United States
S. Mohan
Affiliation:
Courant Institute of Mathematical Sciences and Center for Data Science, New York University, New York, NY, United States
Adrià Marcos-Morales
Affiliation:
Courant Institute of Mathematical Sciences and Center for Data Science, New York University, New York, NY, United States
C. Fernandez-Granda
Affiliation:
Courant Institute of Mathematical Sciences and Center for Data Science, New York University, New York, NY, United States
P. A. Crozier*
Affiliation:
School for the Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, Arizona, United States
*
*Corresponding author: crozier@asu.edu

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. 3024 - 3026
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Copyright
Copyright © Microscopy Society of America 2022

References

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The authors acknowledge funding from NSF (DMR 1840841, OAC 1940263 HDR 1940097, OAC 2103936, HDR 1922658), the Simons Foundation, and the use of facilities of Eyring Materials Center at Arizona State University.Google Scholar