Maier, Pirmin (2017) Modellierung von Erntemengen für Hopfensorten in der Hallertau mittels Deep Learning Algorithmen auf Basis von Klima- und Satellitendaten. Master's, Julius-Maximilians-Universität Würzburg.
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Item URL in elib: | https://elib.dlr.de/116171/ | ||||||
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Document Type: | Thesis (Master's) | ||||||
Title: | Modellierung von Erntemengen für Hopfensorten in der Hallertau mittels Deep Learning Algorithmen auf Basis von Klima- und Satellitendaten | ||||||
Authors: |
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Date: | 20 September 2017 | ||||||
Refereed publication: | No | ||||||
Open Access: | No | ||||||
Gold Open Access: | No | ||||||
In SCOPUS: | No | ||||||
In ISI Web of Science: | No | ||||||
Number of Pages: | 114 | ||||||
Status: | Published | ||||||
Keywords: | Erntemodellierung, Deep Learning, Algorithmen, Hopfen, Hallertau | ||||||
Institution: | Julius-Maximilians-Universität Würzburg | ||||||
Department: | Lehrstuhl für Fernerkdundung | ||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||
HGF - Program: | Space | ||||||
HGF - Program Themes: | Earth Observation | ||||||
DLR - Research area: | Raumfahrt | ||||||
DLR - Program: | R EO - Earth Observation | ||||||
DLR - Research theme (Project): | R - Geoscientific remote sensing and GIS methods | ||||||
Location: | Oberpfaffenhofen | ||||||
Institutes and Institutions: | German Remote Sensing Data Center | ||||||
Deposited By: | Wöhrl, Monika | ||||||
Deposited On: | 04 Dec 2017 11:38 | ||||||
Last Modified: | 04 Dec 2017 11:38 |
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