Michael Steininger

22 papers A* 1A 1C 1Misc 1Journal 12Unranked 5
YearRankTypeTitle / Venue / Authors
2023 J jnl
ConvMOS: climate model output statistics with deep learning.
Data Min. Knowl. Discov.
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho
2023 — —
Deep Learning for Geospatial Environmental Regression (Deep Learning für Regressionsmodelle mit georäumlichen Umweltdaten)
Michael Steininger
2023 A conf
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images.
WACV
Konstantin Kobs, Michael Steininger, Andreas Hotho
2023 — conf
Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks.
LWDA
Melanie Schaller, Michael Steininger, Andrzej Dulny, Daniel Schlör, Andreas Hotho
2023 — conf
Räumliche Erfassung des organischen Kohlenstoffgehaltes von Böden einer landwirtschaftlichen Intensivregion aus Sentinel-2-Daten.
GIL Jahrestagung
Lucas Wittstruck, Heike Gerighausen, Annelie Säurich, Markus Möller, Knut Hartmann, Michael Steininger, Simone Zepp, Thomas Jarmer
2022 J jnl
Do Different Deep Metric Learning Losses Lead to Similar Learned Features?
CoRR
Konstantin Kobs, Michael Steininger, Andrzej Dulny, Andreas Hotho
2022 J jnl
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images.
CoRR
Konstantin Kobs, Michael Steininger, Andreas Hotho
2022 J jnl
Semi-unsupervised Learning for Time Series Classification.
CoRR
Padraig Davidson, Michael Steininger, André Huhn, Anna Krause, Andreas Hotho
2021 J jnl
Anomaly Detection in Beehives: An Algorithm Comparison.
CoRR
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Anna Krause, Andreas Hotho
2021 J jnl
Density-based weighting for imbalanced regression.
Mach. Learn.
Michael Steininger, Konstantin Kobs, Padraig Davidson, Anna Krause, Andreas Hotho
2021 — conf
Detecting Presence Of Speech In Acoustic Data Obtained From Beehives.
DCASE
Pascal Janetzky, Padraig Davidson, Michael Steininger, Anna Krause, Andreas Hotho
2021 A* conf
Do Different Deep Metric Learning Losses Lead to Similar Learned Features?
ICCV
Konstantin Kobs, Michael Steininger, Andrzej Dulny, Andreas Hotho
2021 J jnl
Estimation of Soil Organic Carbon Contents in Croplands of Bavaria from SCMaP Soil Reflectance Composites.
Remote. Sens.
Simone Zepp, Uta Heiden, Martin Bachmann, Martin Wiesmeier, Michael Steininger, Bas van Wesemael
2021 Misc conf
Semi-unsupervised Learning: An In-depth Parameter Analysis.
KI
Padraig Davidson, Florian Buckermann, Michael Steininger, Anna Krause, Andreas Hotho
2020 — conf
Anomaly Detection in Beehives using Deep Recurrent Autoencoders.
SENSORNETS
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho
2020 J jnl
Anomaly Detection in Beehives using Deep Recurrent Autoencoders.
CoRR
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho
2020 J jnl
Deep Learning for Climate Model Output Statistics.
CoRR
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho
2020 J jnl
MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images.
ACM Trans. Spatial Algorithms Syst.
Michael Steininger, Konstantin Kobs, Albin Zehe, Florian Lautenschlager, Martin Becker, Andreas Hotho
2020 J jnl
MapLUR: Exploring a new Paradigm for Estimating Air Pollution using Deep Learning on Map Images.
CoRR
Michael Steininger, Konstantin Kobs, Albin Zehe, Florian Lautenschlager, Martin Becker, Andreas Hotho
2020 — conf
Semi-Supervised Learning for Grain Size Distribution Interpolation.
ICPR Workshops (6)
Konstantin Kobs, Christian Schäfer, Michael Steininger, Anna Krause, Roland Baumhauer, Heiko Paeth, Andreas Hotho
2020 C conf
SimLoss: Class Similarities in Cross Entropy.
ISMIS
Konstantin Kobs, Michael Steininger, Albin Zehe, Florian Lautenschlager, Andreas Hotho
2020 J jnl
SimLoss: Class Similarities in Cross Entropy.
CoRR
Konstantin Kobs, Michael Steininger, Albin Zehe, Florian Lautenschlager, Andreas Hotho