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Christoph Reudenbach
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2020 – today
- 2023
- [j6]Maximilian Kleebauer
, Christopher Marz
Multi-Resolution Segmentation of Solar Photovoltaic Systems Using Deep Learning. Remote. Sens. 15(24): 5687 (2023) - 2022
- [j5]Alice Ziegler
Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro. Remote. Sens. 14(3): 786 (2022) - 2021
- [j4]Maximilian Kleebauer
Semi-Automatic Generation of Training Samples for Detecting Renewable Energy Plants in High-Resolution Aerial Images. Remote. Sens. 13(23): 4793 (2021) - 2020
- [j3]Marvin Ludwig
Quality Assessment of Photogrammetric Methods - A Workflow for Reproducible UAS Orthomosaics. Remote. Sens. 12(22): 3831 (2020)
2010 – 2019
- 2019
- [i1]Hanna Meyer, Christoph Reudenbach, Stephan Wöllauer, Thomas Nauss:
Importance of spatial predictor variable selection in machine learning applications - Moving from data reproduction to spatial prediction. CoRR abs/1908.07805 (2019) - 2018
- [j2]Hanna Meyer
Improving performance of spatio-temporal machine learning models using forward feature selection and target-oriented validation. Environ. Model. Softw. 101: 1-9 (2018) - 2017
- [j1]Hanna Meyer
From local spectral measurements to maps of vegetation cover and biomass on the Qinghai-Tibet-Plateau: Do we need hyperspectral information? Int. J. Appl. Earth Obs. Geoinformation 55: 21-31 (2017)
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