Machine Learning Applied to MSL/Chemcam Data

Authors :: Forni, O.
Gasnault, O.
Cousin, A.
Anderson, R. B.
Dehouck, E.
David, G.
Pinet, P.
Bridges, J. C.
Wiens, R. C.
Maurice, S.
Meslin, P.-Y.
Institut de recherche en astrophysique et planétologie (IRAP)
Institut national des sciences de l'Univers (INSU - CNRS)-Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP)
Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)
Los Alamos National Laboratory (LANL)
Source :: 50th Lunar and Planetary Science Conference, 50th Lunar and Planetary Science Conference, Mar 2019, Houston, United States
Publication Year :: 2019
Publisher :: HAL CCSD, 2019.
Abstract: International audience; We want to test and evaluate the performances in terms of classification and prediction of machine learning techniques applied to the ChemCam data.

Subjects :: [SDU.ASTR.EP]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Earth and Planetary Astrophysics [astro-ph.EP]
[SDU.STU]Sciences of the Universe [physics]/Earth Sciences
[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]

Language :: English
Database :: OpenAIRE
Journal :: 50th Lunar and Planetary Science Conference, 50th Lunar and Planetary Science Conference, Mar 2019, Houston, United States
Accession number :: edsair.dedup.wf.001..706a557b185976c232267739038b7318

Tools