Rafael Sterzinger is a project assistant at the Computer Vision Lab, Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria.
Education |
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| 2020 – 2023 | MSc. ETH Zürich, Machine Intelligence.
Thesis title: . Thesis advisor: Andreas Krause |
| 2017 – 2020 | BSc. TU Wien, Business Informatics. |
Profile
Google Scholar | ArXiv | ORCID | LinkedIn
Publications
R. Sterzinger, W. Koch, R. Hoch, (2024). “Exploring Machine Learning for Faster Mapping and Scheduling of Automotive Applications on ADAS Platforms”, International Conference on Machine Learning and Application – ICMLA 2024, Miami, Florida, USA. (Accepted)
R. Sterzinger, C. Stippel, R. Sablatnig, (2024). “Fusing Forces: Deep-Human-Guided Refinement of Segmentation Masks”, International Conference on Pattern Recognition – ICPR 2024, Kolkata, India. (Accepted)
S. Strohmayer, R. Sterzinger, C. Stippel, M. Kampel, (2024). “Through-Wall Imaging based on WiFi Channel State Information”, 2024 IEEE International Conference on Image Processing – ICIP 2024, Abu Dhabi, UAE. (Accepted)
R. Sterzinger, S. Brenner, R. Sablatnig, (2024). “Drawing the Line: Deep Segmentation for Extracting Art from Ancient Etruscan Mirrors”, In: Barney Smith, E.H., Liwicki, M., Peng, L. (eds) Document Analysis and Recognition – ICDAR 2024, ICDAR 2024, Lecture Notes in Computer Science, vol 14806, Springer, pp. 39-56, doi: https://doi.org/10.1007/978-3-031-70543-4_3
C. Stippel, R. Sterzinger, D. Sengl, A. Bratukhin, M. Kobelrausch, S. Wilker, T. Sauter, (2024). “Online HVAC Optimization under Comfort Constraints via Reinforcement Learning”, 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS), St. Louis, MO, USA, pp. 1-6, doi: https://doi.org/10.1109/ICPS59941.2024.10640003
C. Stippel, T. Heitzinger, R. Sterzinger and M. Kampel, (2024). “Closing the Gap in Human Behavior Analysis: A Pipeline for Synthesizing Trimodal Data”, 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, pp. 793-798, doi: https://doi.org/10.1109/PerComWorkshops59983.2024.10503351
R. Sterzinger, J. Poland, M. B. Paulus and D. Chételat, (2023). “Learning to Predict Security Constraints for Large-Scale Unit Commitment Problems”, 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Grenoble, France, pp. 1-5, doi: https://doi.org/10.1109/ISGTEUROPE56780.2023.10407236
C. Stippel, T. Heitzinger, R. Sterzinger, and M. Kampel, (2023). “From RGB to Depth and Thermal: Mapping between Modalities to Alleviate Data Scarcity”, In the Proceedings of the Austrian Association for Pattern Recognition (AAPR) Joint Austrian Computer Vision and Robotics Workshop, Vienna, Austria. (Accepted)