| Evaluating CNNs on the gestalt principle of closure G Ehrensperger, S Stabinger, AR Sánchez International Conference on Artificial Neural Networks, 296-301, 2019 | 7 | 2019 |
| Accounting for seasonality in the metastatistical extreme value distribution MA Falkensteiner, H Schellander, G Ehrensperger, T Hell Weather and Climate Extremes 42, 100601, 2023 | 1 | 2023 |
| Fast algorithms for morphological operations using run-length encoded binary images G Ehrensperger, A Ostermann, F Schwitzer arXiv preprint arXiv:1504.01052, 2015 | 1 | 2015 |
| Schnelle Algorithmen zur Berechnung von Erosion und Dilatation auf lauflängenkodierten Binärbildern G Ehrensperger Master’s thesis, University of Innsbruck, Dept. Math, 2012 | 1 | 2012 |
| Accounting for seasonality in trends of extreme precipitation H Schellander, MA Falkensteiner, G Ehrensperger, T Hell EGU General Assembly Conference Abstracts, EGU-7626, 2023 | | 2023 |
| Modelling severe hail events over Austria using the metastatistical extreme value distribution MA Falkensteiner, G Ehrensperger, T Simon, T Hell EGU General Assembly Conference Abstracts, EGU-14903, 2023 | | 2023 |
| Identifying Lightning Processes in ERA5 Soundings with Deep Learning T Hell, G Ehrensperger, GJ Mayr, T Simon EGU General Assembly Conference Abstracts, EGU-16098, 2023 | | 2023 |
| Evaluating the generalization ability of a deep learning model trained to detect cloud-to-ground lightning on raw ERA5 data G Ehrensperger, T Hell, GJ Mayr, T Simon EGU General Assembly Conference Abstracts, EGU-15817, 2023 | | 2023 |
| Identifying Lightning Processes in ERA5 Soundings with Deep Learning G Ehrensperger, T Hell, GJ Mayr, T Simon arXiv preprint arXiv:2210.11529, 2022 | | 2022 |
