M.Sc. Fabian Rabe
Phone: | +49 821 598 -2473 |
Email: | fabian.rabe@informatik.uni-augsburginformatik.uni-augsburg.de () |
Room: | 3070 (N) |
Open hours: | https://digicampus.uni-augsburg.de/dispatch.php/profile/index?username=rabefabi_dozent |
Address: | Universitätsstraße 6a, 86159 Augsburg |
Short Curriculum Vitae
- 2015: Bachelor Informatik & Multimedia, University of Augsburg
- 2017: Master Informatik, University of Augsburg
- Since January 2018: Research Assistant, Chair of Software Methodologies for Distributed Systems, University of Augsburg
Fields of Research
- Medical Information Science
- Machine Learning
Mentored Theses
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„Sekundäre Verwendung medizinischer Daten in der Forschung: Untersuchung moderner Lösungsansätze zur Datenbereitstellung unter Verwendung der Stakeholderanalyse“ - Master Thesis
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„Automatic Segmentation of Microscopic Images of Pollen via the Scikit-Image Library“ - Bachelor Thesis
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„Evaluation von Trainingsmethoden zur Erkennung von Netzhauterkrankungen mittels Deep Learning“ - Bachelor Thesis
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„Federated Deep Learning mit medizinischen Daten“ - Master Thesis
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„Automatische Segmentierung von mikroskopischen Bildern von Pollen mittels OpenCV und GrabCut“ - Bachelor Thesis
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„Untersuchung der Effekte von Active Learning auf die Klassifizierung von medizinischen Bildern mittels Deep Learning“ - Master Thesis
Publications
2021 |
Fabian Stieler, Fabian Rabe and Bernhard Bauer. 2021. Towards domain-specific explainable AI: model interpretation of a skin image classifier using a human approach. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2021, 19-25 June 2021, Nashville, TN, USA. IEEE, Piscataway, NJ, 1802-1809 DOI: 10.1109/CVPRW53098.2021.00199 |
2020 |
Fabian Stieler, Fabian Rabe and Bernhard Bauer. 2020. Federated medical data - how much can deep learning models benefit? [Poster]. In AMIA 2020 Virtual Clinical Informatics Converence, May 19-21. |
2019 |
Julian Schiele, Fabian Rabe, Maximilian Schmitt, Manuel Glaser, Franziska Haring, Jens O. Brunner, Bernhard Bauer, Björn Schuller, Claudia Traidl-Hoffmann and Athanasios Damialis. 2019. Automated classification of airborne pollen using neural networks. In Thomas Penzel, Thomas Lenarz, Mohamad Sawan and Riccardo Barbieri (Ed.). 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 23-27 July 2019, Berlin, Germany. IEEE, New York, NY, 4474-4478. DOI: 10.1109/embc.2019.8856910 |
2018 |
Simon Lohmüller, Fabian Rabe, Andrea Fendt, Bernhard Bauer and Lars Christoph Schmelz. 2018. SON function performance prediction in a cognitive SON management system. In Jordi Pérez-Romero and Stephan F. Pfletschinger (Ed.). 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 15-18 April 2018, Barcelona, Spain. IEEE, Piscataway, NJ, 13-18. DOI: 10.1109/wcncw.2018.8368999 |