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Developing Deep Neural Network-based Denoising Techniques for Time-Resolved In Situ TEM of Catalyst Nanoparticles

Published online by Cambridge University Press:  30 July 2021

Joshua Vincent ,
Sreyas Mohan ,
Ramon Manzorro ,
Binh Tang ,
Dev Sheth ,
Mitesh Khapra ,
David Matteson ,
Eero Simoncelli ,
Carlos Fernandez-Granda  and
Peter Crozier
Joshua Vincent
Affiliation:
Arizona State University, United States
Sreyas Mohan
Affiliation:
New York University, United States
Ramon Manzorro
Affiliation:
Arizona State University, United States
Binh Tang
Affiliation:
Cornell University, United States
Dev Sheth
Affiliation:
IIT Madras, United States
Mitesh Khapra
Affiliation:
IIT Madras, United States
David Matteson
Affiliation:
Cornell University, United States
Eero Simoncelli
Affiliation:
New York University, United States
Carlos Fernandez-Granda
Affiliation:
New York University, United States
Peter Crozier
Affiliation:
Arizona State University, Tempe, Arizona, United States

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. 262 - 264
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

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Ede, J., Machine Learning: Science and Technology, (2020), in press.Google Scholar
Vincent, J. L., et al. , in preparation, pre-print at: arXiv :2101.07770, (2021).Google Scholar
Mohan, S., et al. , in preparation, pre-print at: arXiv:2010.12970, (2020).Google Scholar
Sheth, Dev Y., et al. , submitted to CVPR, pre-print at: arXiv:2011.15045, (2020).Google Scholar
We gratefully acknowledge support of NSF grants CBET-1604971, NRT-1922658, CCF-1934985, OAC-1940097, OAC-1940124, and OAC-1940263, and the facilities at ASU's John M. Cowley Center for High Resolution Electron Microscopy.Google Scholar