High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource, 1 online resource.
- Sprache
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Englisch
- Erschienen in
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High-throughput phenotyping for non-destructive estimation of soybean fresh biomass using a machine learning model and temporal UAV data ; volume:19 ; number:1 ; day:26 ; month:8 ; year:2023 ; pages:1-13 ; date:12.2023
Plant methods ; 19, Heft 1 (26.8.2023), 1-13, 12.2023
- Urheber
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Ranđelović, Predrag
Đorđević, Vuk
Miladinović, Jegor
Prodanović, Slaven
Ćeran, Marina
Vollmann, Johann
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1186/s13007-023-01054-6
- URN
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urn:nbn:de:101:1-2023110710185848612340
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 11:00 MESZ
Datenpartner
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Beteiligte
- Ranđelović, Predrag
- Đorđević, Vuk
- Miladinović, Jegor
- Prodanović, Slaven
- Ćeran, Marina
- Vollmann, Johann
- SpringerLink (Online service)
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