| Reliably decoding autoencoders’ latent spaces for one-class learning image inspection scenarios D Soukup, T Pinetz Proceedings of the OAGM Workshop, 90-93, 2018 | 14 | 2018 |
| On the estimation of the Wasserstein distance in generative models T Pinetz, D Soukup, T Pock Pattern Recognition: 41st DAGM German Conference, DAGM GCPR 2019, Dortmund …, 2019 | 10 | 2019 |
| Actual Impact of GAN Augmentation on CNN Classification Performance T Pinetz, J Ruisz, D Soukup ICPRAM, 2019 | 9 | 2019 |
| Reduction of gadolinium-based contrast agents in MRI using convolutional neural networks and different input protocols: limited interchangeability of synthesized sequences with … R Haase, T Pinetz, Z Bendella, E Kobler, D Paech, W Block, A Effland, ... Investigative radiology 58 (6), 420-430, 2023 | 8 | 2023 |
| Shared prior learning of energy-based models for image reconstruction T Pinetz, E Kobler, T Pock, A Effland SIAM Journal on Imaging Sciences 14 (4), 1706-1748, 2021 | 7 | 2021 |
| What is optimized in Wasserstein GANs? T Pinetz, D Soukup, T Pock | 6 | 2018 |
| Impact of the latent space on the ability of GANs to fit the distribution T Pinetz, D Soukup, T Pock | 5 | 2019 |
| Artificial contrast: deep learning for reducing gadolinium-based contrast agents in neuroradiology R Haase, T Pinetz, E Kobler, D Paech, A Effland, A Radbruch, ... Investigative Radiology 58 (8), 539-547, 2023 | 4 | 2023 |
| Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke G Brugnara, M Baumgartner, ED Scholze, K Deike-Hofmann, K Kades, ... Nature Communications 14 (1), 4938, 2023 | 3 | 2023 |
| Using a U-Shaped Neural Network for minutiae extraction trained from refined, synthetic fingerprints T Pinetz, R Huber-Mörk, D Soukop, R Sablatnig Proceedings of the OAGM&ARW Joint Workshop: Vision, Automation and Robotics, 2017 | 3 | 2017 |
| Faithful Synthesis of Low-Dose Contrast-Enhanced Brain MRI Scans Using Noise-Preserving Conditional GANs T Pinetz, E Kobler, R Haase, K Deike-Hofmann, A Radbruch, A Effland International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 2 | 2023 |
| Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy T Pinetz, E Kobler, C Doberstein, B Berkels, A Effland Scale Space and Variational Methods in Computer Vision: 8th International …, 2021 | 1 | 2021 |
| Gadolinium dose reduction for brain MRI using conditional deep learning T Pinetz, E Kobler, R Haase, JA Luetkens, M Meetschen, J Haubold, ... arXiv preprint arXiv:2403.03539, 2024 | | 2024 |
| Faithful Synthesis of Low-Dose Contrast-Enhanced Brain MRI Scans Using Noise-Preserving Conditional GANs H Greenspan, R Taylor, A Madabhushi, K Deike-Hofmann, ... 26th International Conference on Medical Image Computing and Computer …, 2023 | | 2023 |
| Blind Single Image Super-Resolution via Iterated Shared Prior Learning T Pinetz, E Kobler, T Pock, A Effland DAGM German Conference on Pattern Recognition, 151-165, 2022 | | 2022 |
| A variational framework for statistical learning of general inverse problems T Pinetz | | 2021 |
| Learning Fingerprint Munutiae for Biometric Authentication via Deep Networks T Pinetz | | 2017 |
