#Machine Learning

In Machine Learning, artificial systems learn from experience – similar to humans. This technology can be used in various applications in research and practice, for example to analyse medical data or fend off IT attacks.

Projects

Publications

Horst, F., Hoitz, F., Slijepcevic, D., Schons, N., Beckmann, H., Nigg, B. M., & Schöllhorn, W. I. (2023). Identification of subject-specific responses to footwear during running. Scientific Reports, 13(1), 11284. https://doi.org/10.1038/s41598-023-38090-0
Bruckner, Franziska, Feyersinger, Erwin, & Lechner, Patrik. (2023, June 14). AniVision: Machine Learning as a Tool for Studying Animation in Ephemeral Films [Vortrag]. Society for Animation Studies 34th Annual Conference – The Animated Environment, Online – Glassboro. https://www.sas34.org/
Feyersinger, Erwin. (2023, June 14). Animation Studies and Digital Humanities [Vortrag]. Society for Animation Studies 34th Annual Conference – The Animated Environment, Online – Glassboro. https://www.sas34.org/
Feyersinger, Erwin. (2023, August 6). Projektvorstellung AniVision [Vortrag]. Tools und Plattformen in der Praxis – Workshop der DHd AG Film und Video, Online. https://dhdagfilm.hypotheses.org/
Aigner, W. (2023, May 22). Visualization Literacy & Onboarding. VRVis Forum #176 | Digital Humanism, Vienna, Austria. https://www.vrvis.at/news-events/events/176-digital-humanism
Feyersinger, Erwin. (2023, February 3). AniVision: A Digital Humanities Approach to Researching Archives [Vortrag]. Workshop: Archiving and Canonizing Animation. Animation and Contemporary Media Culture., Dresden.
Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Towards more transparency: The utility of Grad-CAM in tracing back deep learning based classification decisions in children with cerebral palsy. Gait & Posture, 100, 32–33. https://doi.org/10.1016/j.gaitpost.2022.11.045
Stoiber, C., Emrich, Š., & Aigner, W. (2023). Design Guidelines for Visualization Onboarding Concepts in Data Journalism [Vortrag]. STS Conference, Graz. https://stsconf.tugraz.at/
Vulpe-Grigorasi, A. (2023). Multimodal machine learning for cognitive load based on eye tracking and biosensors. 2023 Symposium on Eye Tracking Research and Applications, 1–3. https://doi.org/10.1145/3588015.3589534
Vulpe-Grigorasi, A. (2023). Cognitive load assessment based on VR eye-tracking and biosensors. Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia, 589–591. https://doi.org/10.1145/3626705.3632618

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