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Denoising Large In Situ TEM Image Datasets: A Convolutional Neural Network-based Approach

Published online by Cambridge University Press:  30 July 2020

Joshua Vincent ,
Sreyas Mohan ,
Carlos Fernandez-Granda  and
Peter Crozier
Joshua Vincent
Affiliation:
Arizona State University, Tempe, Arizona, United States
Sreyas Mohan
Affiliation:
New York University, New York City, New York, United States
Carlos Fernandez-Granda
Affiliation:
New York University, New York City, New York, United States
Peter Crozier
Affiliation:
Arizona State University, Tempe, Arizona, United States

Abstract

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Type
Advances in Modeling, Simulation, and Artificial Intelligence in Microscopy and Microanalysis for Physical and Biological Systems
Information
Microscopy and Microanalysis , Volume 26 , Supplement S2 , August 2020 , pp. 1720 - 1721
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Copyright
Copyright © Microscopy Society of America 2020

References

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Mohan, S., Kadkhodaie, Z., Simocelli, E. P., and Fernandez-Granda, C., 2019. Robust and Interpretable Blind Image Denoising via Bias-Free Convolutional Neural Networks, preprint available at https://arxiv.org/abs/1906.05478Google Scholar
We gratefully acknowledge support of NSF grants CBET-1604971 and OAC-1940263, and the facilities at ASU's John M. Cowley Center for High Resolution Electron Microscopy.Google Scholar