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Using "Machine Learning" to Make Sense of Very Big and Very Small Data Sets

Helbert, Jörn and Amore, Mario (2020) Using "Machine Learning" to Make Sense of Very Big and Very Small Data Sets. Goldschmidt Conference, Hawaii, USA. doi: 10.46427/gold2020.1014.

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Official URL: https://goldschmidtabstracts.info/abstracts/abstractView?doi=10.46427/gold2020.1014


Item URL in elib:https://elib.dlr.de/138825/
Document Type:Conference or Workshop Item (Speech)
Title:Using "Machine Learning" to Make Sense of Very Big and Very Small Data Sets
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Helbert, JörnJoern.Helbert (at) dlr.dehttps://orcid.org/0000-0001-5346-9505
Amore, MarioMario.DAmore (at) dlr.dehttps://orcid.org/0000-0001-9325-6889
Date:2020
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.46427/gold2020.1014
Page Range:p. 1014
Status:Published
Keywords:Machine Learning, Datenprozessierung, Spektroskopie, Fernerkundung
Event Title:Goldschmidt Conference
Event Location:Hawaii, USA
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Exploration
DLR - Research area:Raumfahrt
DLR - Program:R EW - Space Exploration
DLR - Research theme (Project):R - Project BepiColombo - MERTIS and BELA, R - Venus Emissivity Mapper
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Planetary Research > Planetary Laboratories
Deposited By: Helbert, Dr.rer.nat. Jörn
Deposited On:03 Dec 2020 11:03
Last Modified:03 Dec 2020 11:03

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