Cell Tracking According to Biological Needs - Strong Mitosis-Aware Multi- Hypothesis Tracker With Aleatoric Uncertainty.

Timo Kaiser

Timo Kaiser Maximilian Schier Bodo Rosenhahn Cell Tracking According to Biological Needs - Strong Mitosis-Aware Multi- Hypothesis Tracker With Aleatoric Uncertainty. 4826-4840 2025 December 44 IEEE Trans. Medical Imaging 12 https://doi.org/10.1109/TMI.2025.3583148 db/journals/tmi/tmi44.html#KaiserSR25 streams/journals/tmi

Thomas Norrenbrock Timo Kaiser Sovan Biswas Ramesh Manuvinakurike Bodo Rosenhahn QPM: Discrete Optimization for Globally Interpretable Image Classification. 2025 ICLR https://openreview.net/forum?id=GlAeL0I8LX conf/iclr/2025 db/conf/iclr/iclr2025.html#NorrenbrockKBMR25 Timo Kaiser Thomas Norrenbrock Bodo Rosenhahn UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model. 2025 ICML https://proceedings.mlr.press/v267/kaiser25a.html https://openreview.net/forum?id=G3j3kq7rSC conf/icml/2025 db/conf/icml/icml2025.html#KaiserNR25 Thomas Norrenbrock Timo Kaiser Sovan Biswas Neslihan Kose Ramesh Manuvinakurike Bodo Rosenhahn CHiQPM: Calibrated Hierarchical Interpretable Image Classification. 2025 NeurIPS http://papers.nips.cc/paper_files/paper/2025/hash/15212bd2265c4a3ab0dbc1b1982c1b69-Abstract-Conference.html conf/nips/2025 db/conf/nips/neurips2025.html#NorrenbrockKBKM25

Thomas Norrenbrock Timo Kaiser Sovan Biswas Ramesh Manuvinakurike Bodo Rosenhahn QPM: Discrete Optimization for Globally Interpretable Image Classification. 2025 February abs/2502.20130 CoRR https://doi.org/10.48550/arXiv.2502.20130 db/journals/corr/corr2502.html#abs-2502-20130 streams/journals/corr

Timo Kaiser Thomas Norrenbrock Bodo Rosenhahn UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model. 2025 May abs/2505.05049 CoRR https://doi.org/10.48550/arXiv.2505.05049 db/journals/corr/corr2505.html#abs-2505-05049 streams/journals/corr

Yi Yang Yiming Xu 0005 Timo Kaiser Hao Cheng 0008 Bodo Rosenhahn Michael Ying Yang Multi-Object Tracking Retrieval with LLaVA-Video: A Training-Free Solution to MOT25-StAG Challenge. 2025 November abs/2511.03332 CoRR https://doi.org/10.48550/arXiv.2511.03332 db/journals/corr/corr2511.html#abs-2511-03332 streams/journals/corr

Thomas Norrenbrock Timo Kaiser Sovan Biswas Neslihan Kose Ramesh Manuvinakurike Bodo Rosenhahn CHiQPM: Calibrated Hierarchical Interpretable Image Classification. 2025 November abs/2511.20779 CoRR https://doi.org/10.48550/arXiv.2511.20779 db/journals/corr/corr2511.html#abs-2511-20779 streams/journals/corr

Timo Kaiser Vladimír Ulman Bodo Rosenhahn CHOTA: A Higher Order Accuracy Metric for Cell Tracking. 122-138 2024 ECCV Workshops (16) https://doi.org/10.1007/978-3-031-91721-9_8 conf/eccv/2024-w16 db/conf/eccv/eccv2024-w16.html#KaiserUR24 streams/conf/eccv

Timo Kaiser Maximilian Schier Bodo Rosenhahn Cell Tracking according to Biological Needs - Strong Mitosis-aware Random-finite Sets Tracker with Aleatoric Uncertainty. 2024 abs/2403.15011 CoRR https://doi.org/10.48550/arXiv.2403.15011 db/journals/corr/corr2403.html#abs-2403-15011

Timo Kaiser Vladimír Ulman Bodo Rosenhahn CHOTA: A Higher Order Accuracy Metric for Cell Tracking. 2024 abs/2408.11571 CoRR https://doi.org/10.48550/arXiv.2408.11571 db/journals/corr/corr2408.html#abs-2408-11571 streams/journals/corr

Timo Kaiser Christoph Reinders Bodo Rosenhahn Compensation Learning in Semantic Segmentation. 3267-3278 2023 CVPR Workshops https://doi.org/10.1109/CVPRW59228.2023.00329 conf/cvpr/2023w db/conf/cvpr/cvprw2023.html#KaiserRR23 Patrick Glandorf Timo Kaiser Bodo Rosenhahn HyperSparse Neural Networks: Shifting Exploration to Exploitation through Adaptive Regularization. 1226-1235 2023 ICCV (Workshops) https://doi.org/10.1109/ICCVW60793.2023.00133 conf/iccvw/2023 db/conf/iccvw/iccvw2023.html#GlandorfKR23

Timo Kaiser Christoph Reinders Bodo Rosenhahn Compensation Learning in Semantic Segmentation. 2023 abs/2304.13428 CoRR https://doi.org/10.48550/arXiv.2304.13428 db/journals/corr/corr2304.html#abs-2304-13428

Patrick Glandorf Timo Kaiser Bodo Rosenhahn HyperSparse Neural Networks: Shifting Exploration to Exploitation through Adaptive Regularization. 2023 abs/2308.07163 CoRR https://doi.org/10.48550/arXiv.2308.07163 db/journals/corr/corr2308.html#abs-2308-07163

Timo Kaiser Lukas Ehmann Christoph Reinders Bodo Rosenhahn Blind Knowledge Distillation for Robust Image Classification. 2022 abs/2211.11355 CoRR https://doi.org/10.48550/arXiv.2211.11355 db/journals/corr/corr2211.html#abs-2211-11355

Andrea Hornáková Timo Kaiser Paul Swoboda Michal Rolínek Bodo Rosenhahn Roberto Henschel Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths. 6310-6320 2021 ICCV https://doi.org/10.1109/ICCV48922.2021.00627 conf/iccv/2021 db/conf/iccv/iccv2021.html#HornakovaKSRRH21

Andrea Hornáková Timo Kaiser Paul Swoboda Michal Rolínek Bodo Rosenhahn Roberto Henschel Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths. 2021 abs/2108.10606 CoRR https://arxiv.org/abs/2108.10606 db/journals/corr/corr2108.html#abs-2108-10606

Sovan Biswas Hao Cheng 0008 Lukas Ehmann Patrick Glandorf Roberto Henschel Andrea Hornáková Neslihan Kose Ramesh Manuvinakurike Thomas Norrenbrock Christoph Reinders Michal Rolínek Bodo Rosenhahn Maximilian Schier Paul Swoboda Vladimír Ulman Yiming Xu 0005 Michael Ying Yang Yi Yang