Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-25T18:58:12.956Z Has data issue: false hasContentIssue false
  • English
  • Français

Infrastructure for Analysis of Large Microscopy and Microanalysis Data Sets

Published online by Cambridge University Press:  22 July 2022

Jingrui Wei ,
Carter Francis ,
Dane Morgan ,
KJ Schmidt ,
Aristana Scourtas ,
Ian Foster ,
Ben Blaiszik  and
Paul M. Voyles
Jingrui Wei
Affiliation:
Department of Materials Science and Engineering, University of Wisconsin-Madison, Madison, WI, United States
Carter Francis
Affiliation:
Department of Materials Science and Engineering, University of Wisconsin-Madison, Madison, WI, United States
Dane Morgan
Affiliation:
Department of Materials Science and Engineering, University of Wisconsin-Madison, Madison, WI, United States
KJ Schmidt
Affiliation:
University of Chicago, Globus / Argonne National Laboratory – Data Science and Learning Division
Aristana Scourtas
Affiliation:
University of Chicago, Globus / Argonne National Laboratory – Data Science and Learning Division
Ian Foster
Affiliation:
University of Chicago, Globus / Argonne National Laboratory – Data Science and Learning Division
Ben Blaiszik
Affiliation:
University of Chicago, Globus / Argonne National Laboratory – Data Science and Learning Division
Paul M. Voyles*
Affiliation:
Department of Materials Science and Engineering, University of Wisconsin-Madison, Madison, WI, United States
*
*Corresponding author: paul.voyles@wisc.edu

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. 3094 - 3096
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

hyperspy, DOI: 10.5281/zenodo.5608741CrossRefGoogle Scholar
pxyem, DOI: 10.5281/zenodo.2649351Google Scholar
Foundry: Data, Models, Science, https://ai-materials-and-chemistry.gitbook.io/foundry/Google Scholar
Wilkinson, MD et al. , Scientific Data 3, 160018 (2016). DOI: 10.1038/sdata.2016.18CrossRefGoogle ScholarPubMed
Development of pyxem at UW-Madison is supported by the Wisconsin MRSEC (DMR-1720415). Development of Foundry is support by the National Science Foundation (OAC-1931298).Google Scholar