Daniel Kienzle
Lebenslauf
- Physics in Machine Learning
- Object Localization
- Pose Estimation
- Self-supervised learning
Publikationen
2023 |
Daniel Kienzle, Julian Lorenz, Robin Schön, Katja Ludwig and Rainer Lienhart. 2023. COVID detection and severity prediction with 3D-ConvNeXt and custom pretrainings. In Leonid Karlinsky, Tomer Michaeli, Ko Nishino (Eds.). Computer Vision – ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part VII. Springer, Berlin, 500-516 DOI: 10.1007/978-3-031-25082-8_33 |
Katja Ludwig, Daniel Kienzle, Julian Lorenz and Rainer Lienhart. in press. Detecting arbitrary keypoints on limbs and skis with sparse partly correct segmentation masks. In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (Workshops). IEEE, Piscataway, NJ |
Julian Lorenz, Florian Barthel, Daniel Kienzle and Rainer Lienhart. in press. Haystack: a panoptic scene graph dataset to evaluate rare predicate classes. In IEEE International Conference on Computer Vision Workshops (ICCV 2023 Workshops), October 2-6, 2023, Paris, France. IEEE, New York, NY |
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jegou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matias Nicolas Bossa, Abel Diaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken and Marie-Pierre Revel Dubios. in press. The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. preprint. |
2022 |
Katja Ludwig, Daniel Kienzle and Rainer Lienhart. 2022. Recognition of freely selected keypoints on human limbs. In Rama Chellappa, Jiri Matas, Long Quan, Mubarak Shah, Eric Mortensen (Eds.). 2022 IEEE/CVF International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), New Orleans, LA, USA, 19-24 June 2022. IEEE, Piscataway, NJ, 3530-3538 DOI: 10.1109/CVPRW56347.2022.00397 |
Betreute Abschlussarbeiten
- Clarissa Dinu-Fröhlich, Erstellung von Modellen zur Semantischen Segmentierung von Körperteilen unter Verwendung von schwachen Segementierungsmasken, Projektmodul, Juni 2023
- Jan Claar, Measurement of Droplets in Vaporized Fluids using Machine Learning Techniques, Bachelorarbeit, März 2023
- Jonas Kell, Investigation of transformer architectures for geometrical graph structures and their application to two-dimensional spin systems, Bachelorarbeit, Oktober 2022
- Patrick Hopf, Zeitliche Dynamik in Quantenbillards mit Hilfe neuronaler Netze, Bachelorarbeit, Dezember 2021
Lehre
- WS 2021/22: Grundlagen der Signalverarbeitung und des Maschinellen Lernens
- SS 2022: Machine Learning and Computer Vision
- WS 2022/23: Grundlagen der Signalverarbeitung und des Maschinellen Lernens
- SS 2023: Machine Learning and Computer Vision, Seminar über Multimedia und Maschinelles Sehen, Seminar über Multimediale Datenverarbeitung
- WS 2023/24: Grundlagen der Signalverarbeitung und des Maschinellen Lernens