43 citations · 43 across the 4 of their papers we have counts for
4 papers · 1 filter
Better than Average: Spatially-Aware Aggregation of Segmentation Uncertainty Improves Downstream Performance
Vanessa Emanuela Guarino, Claudia Winklmayr, Jannik Franzen +7
Uncertainty Quantification (UQ) is crucial for ensuring the reliability of automated image segmentations in safety-critical domains like biomedical image analysis or autonomous dri…
PhenoBench: A Comprehensive Benchmark for Cell Phenotyping
Claudia Winklmayr, Jerome Luescher, Nora Koreuber +6
Digital pathology has seen the advent of a wealth of foundational models (FM), yet to date their performance on cell phenotyping has not been benchmarked in a unified manner. We th…
Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification
Jannik Franzen, Claudia Winklmayr, Vanessa E. Guarino +6
Uncertainty Quantification (UQ) is crucial for reliable image segmentation. Yet, while the field sees continual development of novel methods, a lack of agreed-upon benchmarks limit…
BioTracker: An Open-Source Computer Vision Framework for Visual Animal Tracking
Hauke Jürgen Mönck, Andreas Jörg, Tobias von Falkenhausen +7
The study of animal behavior increasingly relies on (semi-) automatic methods for the extraction of relevant behavioral features from video or picture data. To date, several specia…