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Quantifying Feature Uncertainty in Sub-sampled Low-dose (S)TEM Images

Published online by Cambridge University Press:  04 August 2017

Bryan Stanfill ,
Sarah Reehl ,
Maggie Johnson ,
Nigel Browning ,
Layla Mehdi  and
Lisa Bramer
Bryan Stanfill
Affiliation:
National Security Directorate, PNNL, Richland, WA, USA
Sarah Reehl
Affiliation:
National Security Directorate, PNNL, Richland, WA, USA
Maggie Johnson
Affiliation:
Iowa State University, Department of Statistics, AmesUSA
Nigel Browning
Affiliation:
Physical and Computational Science Directorate, PNNL, Richland, WA, USA Materials Science and Engineering, University of Washington, Seattle, WA, USA
Layla Mehdi
Affiliation:
Physical and Computational Science Directorate, PNNL, Richland, WA, USA
Lisa Bramer
Affiliation:
National Security Directorate, PNNL, Richland, WA, USA

Abstract

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Type
Abstract
Information
Microscopy and Microanalysis , Volume 23 , Supplement S1: Proceedings of Microscopy & Microanalysis 2017 , July 2017 , pp. 160 - 161
Copyright
© Microscopy Society of America 2017 

References

[1] Kovarik, L., Stevens, A., Liyu, A., et al, Appl Phys Lett 109(16 2016). p. 164102.CrossRefGoogle Scholar
[2] Stevens, A., Yang, H., Carin, L., et al, Microscopy 63(1 2014). pp. 41.CrossRefGoogle Scholar
[3] Beche, A., Goris, B., Freitag, B., et al, Applied Physics Letters 108(9 2016). p. 093103.Google Scholar
[4] Mehdi, B. L., Qian, J., Nasybulin, E., et al, Nano Letters 15(3 2015). pp. 2168.CrossRefGoogle Scholar
[5] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.Google Scholar