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Schwalb-Willmann, Jakob (2018) A deep learning movement prediction framework for identifying anomalies in animal-environment interactions. Master's, Julius-Maximilians-Universität Würzburg.
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| Item URL in elib: | https://elib.dlr.de/123853/ | ||||||
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| Document Type: | Thesis (Master's) | ||||||
| Title: | A deep learning movement prediction framework for identifying anomalies in animal-environment interactions | ||||||
| Authors: |
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| Date: | 23 October 2018 | ||||||
| Refereed publication: | No | ||||||
| Open Access: | No | ||||||
| Gold Open Access: | No | ||||||
| In SCOPUS: | No | ||||||
| In ISI Web of Science: | No | ||||||
| Number of Pages: | 55 | ||||||
| Status: | Published | ||||||
| Keywords: | movement prediction, framework, anomalis in animal-enviroment | ||||||
| Institution: | Julius-Maximilians-Universität Würzburg | ||||||
| Department: | Lehrstuhl für Fernerkundung | ||||||
| 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: | 29 Nov 2018 09:36 | ||||||
| Last Modified: | 13 Dec 2018 12:16 |
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