Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-23T07:54:35.510Z Has data issue: false hasContentIssue false
  • English
  • Français

Unmixing Mineral Phases, Improving Quantification: Use Machine Learning to Understand Deep-Mantle with STEM-EDS Data

Published online by Cambridge University Press:  22 July 2022

Hui Chen ,
James Badro ,
Duncan T.L. Alexander  and
Cécile Hébert
Hui Chen*
Affiliation:
Electron Spectrometry and Microscopy Laboratory (LSME), IPHYS, EPFL, Lausanne, Switzerland
James Badro
Affiliation:
Earth and Planetary Science Laboratory (EPSL), IPHYS, EPFL, Lausanne, Switzerland Institute de Physique du Globe de Paris, Sorbonne Paris Cité, Paris, France
Duncan T.L. Alexander
Affiliation:
Electron Spectrometry and Microscopy Laboratory (LSME), IPHYS, EPFL, Lausanne, Switzerland
Cécile Hébert
Affiliation:
Electron Spectrometry and Microscopy Laboratory (LSME), IPHYS, EPFL, Lausanne, Switzerland
*
*Corresponding author: [email protected]

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
Quantitative and Qualitative Mapping of Materials
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 542 - 544
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

Jordan, MI and Mitchell, TM, Science, 349 (2015), p. 255. doi:10.1126/science.aaa8415CrossRefGoogle Scholar
Lee, DD and Seung, HS, Nature, 401 (1999), p. 788. doi:10.1038/44565CrossRefGoogle Scholar
Boykov, Y, Veksler, O and Zabih, R, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23 (2001), p. 1222. doi:10.1109/34.969114CrossRefGoogle Scholar
Heinz, DC and Chang, Chein-I, IEEE Transactions on Geoscience and Remote Sensing, 39 (2001), p. 529. doi:10.1109/36.911111CrossRefGoogle Scholar