47 citations · 49 across the 4 of their papers we have counts for
4 papers
There Are No Data Like More Data- Datasets for Deep Learning in Earth Observation
Michael Schmitt, Seyed Ali Ahmadi, Yonghao Xu +4
Carefully curated and annotated datasets are the foundation of machine learning, with particularly data-hungry deep neural networks forming the core of what is often called Artific…
Probabilistic MIMO U-Net: Efficient and Accurate Uncertainty Estimation for Pixel-wise Regression
Anton Baumann, Thomas Roßberg, Michael Schmitt
Uncertainty estimation in machine learning is paramount for enhancing the reliability and interpretability of predictive models, especially in high-stakes real-world scenarios. Des…
Explaining Multimodal Data Fusion: Occlusion Analysis for Wilderness Mapping
Burak Ekim, Michael Schmitt
Jointly harnessing complementary features of multi-modal input data in a common latent space has been found to be beneficial long ago. However, the influence of each modality on th…
MapInWild: A Remote Sensing Dataset to Address the Question What Makes Nature Wild
Burak Ekim, Timo T. Stomberg, Ribana Roscher +1
Antrophonegic pressure (i.e. human influence) on the environment is one of the largest causes of the loss of biological diversity. Wilderness areas, in contrast, are home to undist…