Hostname: page-component-788cddb947-2s2w2 Total loading time: 0 Render date: 2024-10-18T08:08:55.696Z Has data issue: false hasContentIssue false
  • English
  • Français

Artificial Neural Network for Automatic Alignment of Electron Optical Devices

Published online by Cambridge University Press:  22 July 2022

Enzo Rotunno  and
Vincenzo Grillo
Enzo Rotunno*
Affiliation:
Consiglio Nazionale delle Ricerche, Istituto NANO, Modena, Italy
Vincenzo Grillo
Affiliation:
Consiglio Nazionale delle Ricerche, Istituto NANO, Modena, Italy
*
*Corresponding author: enzo.rotunno@nano.cnr.it

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 3010 - 3012
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

Tavabi, A. H., et al. Phys. Rev. Research, 2 (2020), 013185.CrossRefGoogle Scholar
Tavabi, A.H. et al. Phys. Rev. Lett. 126 (2021), 094802CrossRefGoogle Scholar
Ruffato, G, et al. Phys. Rev. Applied 15, (2021) 054028Google Scholar
Simonyan, K., et al. arXiv:1409.1556v6.Google Scholar
Rotunno, E., et al. Ultramicroscopy 228 (2021), 113338CrossRefGoogle Scholar
We acknowledge that this work has been conducted collaboration with Forschungszentrum Jülich, Thermofisher Scientific, and CNR-NANO personnel.Google Scholar