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Diagnostic and Correction of Phase Aberrations in Scanning Transmission Microscopy by Artificial Neural Networks

Published online by Cambridge University Press:  22 July 2022

Giovanni Bertoni*
Affiliation:
Istituto Nanoscienze, Consiglio Nazionale delle Ricerche, Modena, Italy
Enzo Rotunno
Affiliation:
Istituto Nanoscienze, Consiglio Nazionale delle Ricerche, Modena, Italy
Daan Marsmans
Affiliation:
Thermo Fisher Scientific, Eindhoven, Netherlands
Peter Tiemeijer
Affiliation:
Thermo Fisher Scientific, Eindhoven, Netherlands
Vincenzo Grillo
Affiliation:
Istituto Nanoscienze, Consiglio Nazionale delle Ricerche, Modena, Italy
*
*Corresponding author: [email protected]

Abstract

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Type
On Demand - Artificial Intelligence, Instrument Automation, and High-Dimensional Data Analytics for Microscopy and Microanalysis
Copyright
Copyright © Microscopy Society of America 2022

References

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Lupini, AR et al. , Ultramicroscopy 110 (2010), p. 891-898. doi:10.1016/j.ultramic.2010.04.006CrossRefGoogle Scholar
Schnitzer, N et al. , Microscopy Today 27 (2019), p. 12-15. doi:10.1017/S1551929519000427CrossRefGoogle Scholar
The authors acknowledge funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 964591 ‘SMART-electron’.Google Scholar