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2020 – today
- 2024
[j1]Dennis Eschweiler
, Rüveyda Yilmaz, Matisse Baumann, Ina Laube, Rijo Roy, Abin Jose, Daniel Brückner, Johannes Stegmaier:
Denoising diffusion probabilistic models for generation of realistic fully-annotated microscopy image datasets. PLoS Comput. Biol. 20(2) (2024)- 2023
- [c5]Abin Jose, Rijo Roy, Dennis Eschweiler, Ina Laube, Reza Azad, Daniel Moreno-Andrés, Johannes Stegmaier:
End-to-End Classification of Cell-Cycle Stages with Center-Cell Focus Tracker Using Recurrent Neural Networks. ICASSP 2023: 1-5 - [c4]Zhu Chen, Ina Laube, Johannes Stegmaier:
Unsupervised Learning for Feature Extraction and Temporal Alignment of 3D+t Point Clouds of Zebrafish Embryos. MICCAI (8) 2023: 603-612 - 2022
- [c3]Abin Jose, Qi Mei, Dennis Eschweiler, Ina Laube, Johannes Stegmaier:
Linear Discriminant Analysis Metric Learning Using Siamese Neural Networks. ICIP 2022: 3641-3645 - 2021
- [c2]Philipp Gräbel, Ina Laube, Martina Crysandt, Reinhild Herwartz, Melanie Baumann, Barbara Mara Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof:
Rotation Invariance for Unsupervised Cell Representation Learning - Analysis of The Impact of Enforcing Rotation Invariance or Equivariance on Representation for Cell Classification. Bildverarbeitung für die Medizin 2021: 42-47 - [c1]Philipp Gräbel, Ina Laube, Martina Crysandt, Reinhild Herwartz, Melanie Baumann, Barbara Mara Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof:
Surrounding Cell Suppression For Unsupervised Representation Learning In Hematological Cell Classification. ISBI 2021: 526-530
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