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, 2020-06-21 - 2020-06-26, 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:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Helbert, Jörn	UNSPECIFIED	https://orcid.org/0000-0001-5346-9505	UNSPECIFIED
Amore, Mario	UNSPECIFIED	https://orcid.org/0000-0001-9325-6889	UNSPECIFIED

Date:

2020

Refereed publication:

Open Access:

Yes

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

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

Event Start Date:

21 June 2020

Event End Date:

26 June 2020

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:

23 Jul 2024 13:50

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