Publikationen

Assessing Political Bias in Large Language Models
Rettenberger, L.; Schutera, M.; Reischl, M.
2024. arxiv. doi:10.48550/arXiv.2405.13041

Fault Detection in 3D-Printing with Deep Learning
Rettenberger, L.; Beyer, N.; Sieber, I.; Reischl, M.
2024. 2024 IEEE International Conference on Consumer Electronics (ICCE), 4 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCE59016.2024.10444198

Uncertainty-aware particle segmentation for electron microscopy at varied length scales
Rettenberger, L.; Szymanski, N. J.; Zeng, Y.; Schuetzke, J.; Wang, S.; Ceder, G.; Reischl, M.
2024. npj Computational Materials, 10 (1), Artkl.Nr.: 124. doi:10.1038/s41524-024-01302-w

Image-based identification of optical quality and functional properties in inkjet-printed electronics using machine learning
Polomoshnov, M.; Reichert, K.-M.; Rettenberger, L.; Ungerer, M.; Hernandez-Sosa, G.; Gengenbach, U.; Reischl, M.
2024. Journal of Intelligent Manufacturing. doi:10.1007/s10845-024-02385-4

Entomoscope: An Open-Source Photomicroscope for Biodiversity Discovery
Wührl, L.; Rettenberger, L.; Meier, R.; Hartop, E.; Graf, J.; Pylatiuk, C.
2024. IEEE Access, 12, 11785–11794. doi:10.1109/ACCESS.2024.3355272

A Lightweight Framework for Semantic Segmentation of Biomedical Images
Münke, F. R.; Rettenberger, L.; Popova, A.; Reischl, M.
2023. Current Directions in Biomedical Engineering, 9 (1), 190–193. doi:10.1515/cdbme-2023-1048

Mask R-CNN Outperforms U-Net in Instance Segmentation for Overlapping Cells
Rettenberger, L.; Münke, F. R.; Bruch, R.; Reischl, M.
2023. Current Directions in Biomedical Engineering, 9 (1), 335–338. doi:10.1515/cdbme-2023-1084

Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation
Rettenberger, L.; Schilling, M.; Elser, S.; Boehland, M.; Reischl, M.
2023. IEEE Transactions on Biomedical Engineering, 70 (9), 2519–2528. doi:10.1109/TBME.2023.3252889

A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris)
Borlinghaus, P.; Tausch, F.; Rettenberger, L.
2023. Smart Agricultural Technology, 3, Art.-Nr.: 100135. doi:10.1016/j.atech.2022.100135

Improving generative adversarial networks for patch-based unpaired image-to-image translation
Böhland, M.; Bruch, R.; Bäuerle, S.; Rettenberger, L.; Reischl, M.
2023. IEEE Access, 11, 127895–127906. doi:10.1109/ACCESS.2023.3331819

Automated Zebrafish Phenotype Pattern Recognition: 6 Years Ago, and Now
Schutera, M.; Rettenberger, L.; Reischl, M.
2022. Zebrafish, 19 (6), 213–217. doi:10.1089/zeb.2022.0027

Annotation Efforts in Image Segmentation can be Reduced by Neural Network Bootstrapping
Rettenberger, L.; Schilling, M.; Reischl, M.
2022. Current Directions in Biomedical Engineering, 8 (2), 329–332. doi:10.1515/cdbme-2022-1084

Impact of Annotation Noise on Histopathology Nucleus Segmentation
Schilling, M. P.; Ahuja, N.; Rettenberger, L.; Scherr, T.; Reischl, M.
2022. Current Directions in Biomedical Engineering, 8 (2), 197–200. doi:10.1515/cdbme-2022-1051

How automation, machine learning, and DNA barcoding can accelerate species discovery in “dark taxa”: Robotics and AI
Wührl, L.; Pylatiuk, C.; Rettenberger, L.; Meier, R.
2022, Juli 19. 26th International Congress of Entomology (2022), Helsinki, Finnland, 17.–22. Juli 2022

A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris)
Tausch, F.; Borlinghaus, P.; Rettenberger, L.; Reischl, M.
2022, Juni 19. IEEE / CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA, 19.–24. Juni 2022

Methods for the frugal labeler: Multi-class semantic segmentation on heterogeneous labels
Schutera, M.; Rettenberger, L.; Pylatiuk, C.; Reischl, M.
2022. PLoS ONE, 17 (2), Art.-Nr.: e0263656. doi:10.1371/journal.pone.0263656

Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks
Schilling, M. P.; Rettenberger, L.; Münke, F.; Cui, H.; Popova, A. A.; Levkin, P. A.; Mikut, R.; Reischl, M.
2021, November 26. 31. Workshop Computational Intelligence (2021), Berlin, Deutschland, 25.–26. November 2021

Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks
Schilling, M. P.; Rettenberger, L.; Münke, F.; Cui, H.; Popova, A. A.; Levkin, P. A.; Mikut, R.; Reischl, M.
2021. Proceedings - 31. Workshop Computational Intelligence : Berlin, 25. - 26. November 2021. Hrsg.: H. Schulte; F. Hoffmann; R. Mikut, 211–234, KIT Scientific Publishing