4 citations · 5 across the 3 of their papers we have counts for
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cs.CV2026
Finally Outshining the Random Baseline: A Simple and Effective Solution for Active Learning in 3D Biomedical Imaging
Carsten T. Lüth, Jeremias Traub, Kim-Celine Kahl +6
Active learning (AL) has the potential to drastically reduce annotation costs in 3D biomedical image segmentation, where expert labeling of volumetric data is both time-consuming a…
cs.CV2024★ 4 cited
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
Lukas Klein, Carsten T. Lüth, Udo Schlegel +3
Explainable AI (XAI) is a rapidly growing domain with a myriad of proposed methods as well as metrics aiming to evaluate their efficacy. However, current studies are often of limit…