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Machine Learning Applied to MSL/Chemcam Data

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O. Forni
Institut de recherche en astrophysique et planétologie
O. Gasnault
Institut de recherche en astrophysique et planétologie
A. Cousin
  • Function : Author
R. B. Anderson
  • Function : Author
E. Dehouck
  • Function : Author
G. David
  • Function : Author
P. Pinet
J. C. Bridges
  • Function : Author
R. C. Wiens
Los Alamos National Laboratory
S. Maurice
  • Function : Author
P.-Y. Meslin

Abstract

We want to test and evaluate the performances in terms of classification and prediction of machine learning techniques applied to the ChemCam data.

Domains

Sciences of the Universe [physics] Astrophysics [astro-ph] Earth and Planetary Astrophysics [astro-ph.EP] Physics [physics] Astrophysics [astro-ph] Sciences of the Universe [physics] Earth Sciences

Olivier FORNI  : Connect in order to contact the contributor

https://hal-cnrs.archives-ouvertes.fr/hal-02347616

Submitted on : Tuesday, November 5, 2019-11:25:34 AM

Last modification on : Wednesday, November 16, 2022-11:46:09 AM

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Dates and versions

hal-02347616 , version 1 (05-11-2019)

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Cite

O. Forni, O. Gasnault, A. Cousin, R. B. Anderson, E. Dehouck, et al.. Machine Learning Applied to MSL/Chemcam Data. 50th Lunar and Planetary Science Conference, Mar 2019, Houston, United States. ⟨hal-02347616⟩

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