2 citations · 2 across the 6 of their papers we have counts for
6 papers
Galaxy Morphology Classification with Counterfactual Explanation
Zhuo Cao, Lena Krieger, Hanno Scharr +1
Galaxy morphologies play an essential role in the study of the evolution of galaxies. The determination of morphologies is laborious for a large amount of data giving rise to machi…
Equivariant Representation Learning for Augmentation-based Self-Supervised Learning via Image Reconstruction
Qin Wang, Kai Krajsek, Hanno Scharr
Augmentation-based self-supervised learning methods have shown remarkable success in self-supervised visual representation learning, excelling in learning invariant features but of…
Retrieval of sun-induced plant fluorescence in the O-A absorption band from DESIS imagery
Jim Buffat, Miguel Pato, Kevin Alonso +7
We provide the first method allowing to retrieve spaceborne SIF maps at 30 m ground resolution with a strong correlation () to high-quality airborne estimates of sun-induc…
Untrained Perceptual Loss for image denoising of line-like structures in MR images
Elisabeth Pfaehler, Daniel Pflugfelder, Hanno Scharr
In the acquisition of Magnetic Resonance (MR) images shorter scan times lead to higher image noise. Therefore, automatic image denoising using deep learning methods is of high inte…
Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics
J. Seiffarth, L. Blöbaum, R. D. Paul +6
Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnol…
Robust Approximate Characterization of Single-Cell Heterogeneity in Microbial Growth
Richard D. Paul, Johannes Seiffarth, Hanno Scharr +1
Live-cell microscopy allows to go beyond measuring average features of cellular populations to observe, quantify and explain biological heterogeneity. Deep Learning-based instance…