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Tim Prangemeier
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2020 – today
- 2024
- [c9]Christoph Reich, Biplob Debnath, Deep Patel, Tim Prangemeier, Daniel Cremers, Srimat Chakradhar:
Deep Video Codec Control for Vision Models. CVPR Workshops 2024: 5732-5741 - 2023
- [c8]Christoph Reich, Tim Prangemeier, André O. Françani, Heinz Koeppl:
An Instance Segmentation Dataset of Yeast Cells in Microstructures. EMBC 2023: 1-4 - [c7]Christoph Reich, Tim Prangemeier, Heinz Koeppl:
The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures. ICCV (Workshops) 2023: 3942-3953 - [i9]Christoph Reich, Tim Prangemeier, André O. Françani, Heinz Koeppl:
An Instance Segmentation Dataset of Yeast Cells in Microstructures. CoRR abs/2304.07597 (2023) - [i8]Christoph Reich, Tim Prangemeier, Heinz Koeppl:
The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures. CoRR abs/2308.12116 (2023) - [i7]Christoph Reich, Biplob Debnath, Deep Patel, Tim Prangemeier, Srimat Chakradhar:
Deep Video Codec Control. CoRR abs/2308.16215 (2023) - 2022
- [j1]Tim Prangemeier, Christian Wildner, André O. Françani, Christoph Reich, Heinz Koeppl:
Yeast cell segmentation in microstructured environments with deep learning. Biosyst. 211: 104557 (2022) - [c6]Ahmet Gokberk Gul, Özdemir Çetin, Christoph Reich, Nadine Flinner, Tim Prangemeier, Heinz Koeppl:
Histopathological image classification based on self-supervised vision transformer and weak labels. Digital and Computational Pathology 2022 - [i6]Ahmet Gokberk Gul, Özdemir Çetin, Christoph Reich, Tim Prangemeier, Nadine Flinner, Heinz Koeppl:
Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak Labels. CoRR abs/2210.09021 (2022) - 2021
- [c5]Christoph Reich, Tim Prangemeier, Özdemir Çetin, Heinz Koeppl:
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data. BMVC 2021: 429 - [c4]Christoph Reich, Tim Prangemeier, Christian Wildner, Heinz Koeppl:
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy. MICCAI (8) 2021: 476-486 - [i5]Tim Prangemeier, Christian Wildner, Maleen Hanst, Heinz Koeppl:
Maximizing Information Gain for the Characterization of Biomolecular Circuits. CoRR abs/2101.02924 (2021) - [i4]Tim Prangemeier, Christoph Reich, Christian Wildner, Heinz Koeppl:
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy. CoRR abs/2106.08285 (2021) - [i3]Christoph Reich, Tim Prangemeier, Özdemir Çetin, Heinz Koeppl:
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data. CoRR abs/2110.10640 (2021) - 2020
- [c3]Tim Prangemeier, Christoph Reich, Heinz Koeppl:
Attention-Based Transformers for Instance Segmentation of Cells in Microstructures. BIBM 2020: 700-707 - [c2]Tim Prangemeier, Christian Wildner, André O. Françani, Christoph Reich, Heinz Koeppl:
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning. CIBCB 2020: 1-8 - [i2]Tim Prangemeier, Christian Wildner, André O. Françani, Christoph Reich, Heinz Koeppl:
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning. CoRR abs/2011.08062 (2020) - [i1]Tim Prangemeier, Christoph Reich, Heinz Koeppl:
Attention-Based Transformers for Instance Segmentation of Cells in Microstructures. CoRR abs/2011.09763 (2020)
2010 – 2019
- 2018
- [c1]Tim Prangemeier, Christian Wildner, Maleen Hanst, Heinz Koeppl:
Maximizing information gain for the characterization of biomolecular circuits. NANOCOM 2018: 1:1-1:6
Coauthor Index
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