| Issue Date | Title | Involved Person(s) |
| 30-Mar-2023 | Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks | Amirian, Mohammadreza; Montoya-Zegarra, Javier A.; Herzig, Ivo; Eggenberger Hotz, Peter; Lichtensteiger, Lukas, et al |
| 9-Jun-2022 | Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT | Herzig, Ivo; Paysan, Pascal; Scheib, Stefan; Züst, Alexander; Schilling, Frank-Peter, et al |
| 13-May-2022 | Foundations of Data Science : a comprehensive overview formed at the 1st International Symposium on the Science of Data Science | Schilling, Frank-Peter; Flumini, Dandolo; Füchslin, Rudolf Marcel; Gavagnin, Elena; Geller, Armando, et al |
| 9-Jun-2021 | A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications | Simmler, Niclas; Sager, Pascal; Andermatt, Philipp; Chavarriaga, Ricardo; Schilling, Frank-Peter, et al |
| Mar-2021 | Two to trust : AutoML for safe modelling and interpretable deep learning for robustness | Amirian, Mohammadreza; Tuggener, Lukas; Chavarriaga, Ricardo; Satyawan, Yvan Putra; Schilling, Frank-Peter, et al |
| 6-Nov-2020 | Design patterns for resource-constrained automated deep-learning methods | Tuggener, Lukas; Amirian, Mohammadreza; Benites de Azevedo e Souza, Fernando; von Däniken, Pius; Gupta, Prakhar, et al |
| 15-May-2019 | Deep Learning in medizinischer Diagnostik und Qualitätskontrolle | Stadelmann, Thilo; Schilling, Frank-Peter |
| 2019 | Efficient deep CNNs for cross-modal automated computer vision under time and space constraints | Amirian, Mohammadreza; Rombach, Katharina; Tuggener, Lukas; Schilling, Frank-Peter; Stadelmann, Thilo |
