Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks. - Marcel P. Schilling; Luca Rettenberger; Friedrich R. Münke; Haijun Cui; Anna A. Popova; Pavel A. Levkin; Ralf Mikut; Markus Reischl (CoRR, 2021)

Improving Generative Adversarial Networks for Patch-Based Unpaired Image-to-Image Translation. - Moritz Böhland; Roman Bruch; Simon Bäuerle; Luca Rettenberger; Markus Reischl (IEEE Access, 2023)

Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation. - Luca Rettenberger; Marcel P. Schilling; Stefan Elser; Moritz Böhland; Markus Reischl (IEEE Trans. Biomed. Eng., 2023)

Fault Detection in 3D-Printing with Deep Learning. - Luca Rettenberger; Nils Beyer; Ingo Sieber; Markus Reischl (ICCE, 2024)

Entomoscope: An Open-Source Photomicroscope for Biodiversity Discovery. - Lorenz Wührl; Luca Rettenberger; Rudolf Meier; Emily Hartop; Julien Graf; Christian Pylatiuk (IEEE Access, 2024)

Image-based identification of optical quality and functional properties in inkjet-printed electronics using machine learning. - Maxim Polomoshnov; Klaus-Martin Reichert; Luca Rettenberger; Martin Ungerer; Gerardo Hernandez-Sosa; Ulrich Gengenbach; Markus Reischl (J. Intell. Manuf., 2025)

Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters. - David Exler; Mark Schutera; Markus Reischl; Luca Rettenberger (CoRR, 2025)

Assessing political bias in large language models. - Luca Rettenberger; Markus Reischl; Mark Schutera (J. Comput. Soc. Sci., 2025)