Assessment of the uncertainty and interpretability of deep learning models for mapping soil salinity using DeepQuantreg and game theory
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2045-2322
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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online resource.
- Erschienen in
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Assessment of the uncertainty and interpretability of deep learning models for mapping soil salinity using DeepQuantreg and game theory ; volume:12 ; number:1 ; day:7 ; month:9 ; year:2022 ; pages:1-12 ; date:12.2022
Scientific reports ; 12, Heft 1 (7.9.2022), 1-12, 12.2022
- Urheber
-
Mohammadifar, Aliakbar
Gholami, Hamid
Golzari, Shahram
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-022-19357-4
- URN
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urn:nbn:de:101:1-2022112421333893909106
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:31 MESZ
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Beteiligte
- Mohammadifar, Aliakbar
- Gholami, Hamid
- Golzari, Shahram
- SpringerLink (Online service)
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