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Michael Steininger
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2020 – today
- 2023
- [b1]Michael Steininger:
Deep Learning for Geospatial Environmental Regression (Deep Learning für Regressionsmodelle mit georäumlichen Umweltdaten). Würzburg University, Germany, 2023 - [j4]Michael Steininger
, Daniel Abel
ConvMOS: climate model output statistics with deep learning. Data Min. Knowl. Discov. 37(1): 136-166 (2023) - [c9]Lucas Wittstruck, Heike Gerighausen, Annelie Säurich, Markus Möller, Knut Hartmann, Michael Steininger, Simone Zepp, Thomas Jarmer:
Räumliche Erfassung des organischen Kohlenstoffgehaltes von Böden einer landwirtschaftlichen Intensivregion aus Sentinel-2-Daten. GIL Jahrestagung 2023: 531-536 - [c8]Melanie Schaller, Michael Steininger, Andrzej Dulny, Daniel Schlör, Andreas Hotho:
Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks. LWDA 2023: 454-469 - [c7]Konstantin Kobs, Michael Steininger, Andreas Hotho:
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images. WACV 2023: 1063-1072 - 2022
- [i8]Konstantin Kobs, Michael Steininger, Andrzej Dulny, Andreas Hotho:
Do Different Deep Metric Learning Losses Lead to Similar Learned Features? CoRR abs/2205.02698 (2022) - [i7]Padraig Davidson, Michael Steininger, André Huhn, Anna Krause, Andreas Hotho:
Semi-unsupervised Learning for Time Series Classification. CoRR abs/2207.03119 (2022) - [i6]Konstantin Kobs, Michael Steininger, Andreas Hotho:
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images. CoRR abs/2211.12760 (2022) - 2021
- [j3]Michael Steininger
Density-based weighting for imbalanced regression. Mach. Learn. 110(8): 2187-2211 (2021) - [j2]Simone Zepp
Estimation of Soil Organic Carbon Contents in Croplands of Bavaria from SCMaP Soil Reflectance Composites. Remote. Sens. 13(16): 3141 (2021) - [c6]Pascal Janetzky, Padraig Davidson, Michael Steininger, Anna Krause, Andreas Hotho:
Detecting Presence Of Speech In Acoustic Data Obtained From Beehives. DCASE 2021: 26-30 - [c5]Konstantin Kobs, Michael Steininger, Andrzej Dulny, Andreas Hotho:
Do Different Deep Metric Learning Losses Lead to Similar Learned Features? ICCV 2021: 10624-10634 - [c4]Padraig Davidson, Florian Buckermann, Michael Steininger, Anna Krause, Andreas Hotho:
Semi-unsupervised Learning: An In-depth Parameter Analysis. KI 2021: 51-66 - [i5]Padraig Davidson, Michael Steininger, Florian Lautenschlager, Anna Krause, Andreas Hotho:
Anomaly Detection in Beehives: An Algorithm Comparison. CoRR abs/2110.03945 (2021) - 2020
- [j1]Michael Steininger
MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images. ACM Trans. Spatial Algorithms Syst. 6(3): 19:1-19:24 (2020) - [c3]Konstantin Kobs, Christian Schäfer
Semi-Supervised Learning for Grain Size Distribution Interpolation. ICPR Workshops (6) 2020: 34-44 - [c2]Konstantin Kobs, Michael Steininger, Albin Zehe, Florian Lautenschlager, Andreas Hotho:
SimLoss: Class Similarities in Cross Entropy. ISMIS 2020: 431-439 - [c1]Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho:
Anomaly Detection in Beehives using Deep Recurrent Autoencoders. SENSORNETS 2020: 142-149 - [i4]Michael Steininger, Konstantin Kobs, Albin Zehe, Florian Lautenschlager, Martin Becker, Andreas Hotho:
MapLUR: Exploring a new Paradigm for Estimating Air Pollution using Deep Learning on Map Images. CoRR abs/2002.07493 (2020) - [i3]Konstantin Kobs, Michael Steininger, Albin Zehe, Florian Lautenschlager, Andreas Hotho:
SimLoss: Class Similarities in Cross Entropy. CoRR abs/2003.03182 (2020) - [i2]Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause
Anomaly Detection in Beehives using Deep Recurrent Autoencoders. CoRR abs/2003.04576 (2020) - [i1]Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho:
Deep Learning for Climate Model Output Statistics. CoRR abs/2012.10394 (2020)
Coauthor Index
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