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Machine Learning for Sub-pixel Super-resolution in Direct Electron Detectors

Published online by Cambridge University Press:  30 July 2020

Gabriela Correa  and
David Muller
Gabriela Correa
Affiliation:
Cornell University, Ithaca, New York, United States
David Muller
Affiliation:
Cornell University, Ithaca, New York, United States

Abstract

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Type
Pushing the Limits of Detection in Quantitative (S)TEM Imaging, EELS, and EDX
Information
Microscopy and Microanalysis , Volume 26 , Supplement S2 , August 2020 , pp. 1932 - 1934
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Copyright
Copyright © Microscopy Society of America 2020

References

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This work used resources provided by the National Science Foundation Platform for the Accelerated Realization, Analysis, and Discovery of Interface Materials (PARADIM) under Cooperative Agreement No. NSF-DMR-1539918, and resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. GCC acknowledges support by the Alfred P. Sloan Foundation and Department of Energy Computational Science Graduate Fellowship (DOE CSGF), which is provided under grant number DE-FG02-97ER25308.Google Scholar