Publikationen: Institut für Creative\Media/Technologies - Institut für Creative\Media/Technologies

Vasof, A., Bruckner, F., Gürtler, C., Schmid, C., Husinsky, M., Zeller, M., Munk, C., Salhofer, J., Schoiswohl, P., Brullo, R., Nguyen-Thi-Minh, H., & Schmidt, R. (2024). VRinMotion – ExperiMotion 3 [VR – Installation].

Bibtex

Vulpe-Grigorasi, A., Kren, Z., Slijepčević, D., Schmied, R., & Leung, V. (2024). Attention performance classification based on eye tracking and machine learning. Informatics 2024 Proceedings. IEEE International Scientific Conference on Informatics, Poprad Slovakia. https://doi.org/10.1109/Informatics62280.2024.10900810

C. Jandl, T. Moser, & S. Schlund. (2024, September 25). Indicator-based Potential Analysis for Asset Tracking Applications [Article]. 10th International Conference on Sensors Engineering and Electronics Instrumentation Advances (SEIA" 2024), Ibiza (Balearic Islands), Spain. http://dx.doi.org/10.13140/RG.2.2.36670.50243

Altendorfer, K., & Felberbauer, T. (2023). Forecast and production order accuracy for stochastic forecast updates with demand shifting and forecast bias correction. Simulation Modelling Practice and Theory, 125, 102740. https://doi.org/10.1016/j.simpat.2023.102740

Belinskaya, Y. (2023). ‘Insider news’ on Russian Telegram: Resembling truth, proximity and objectivity. Journal of Applied Journalism & Media Studies. https://doi.org/10.1386/ajms_00108_1

Belinskaya, Y. (2023). How the internet is being tamed in Russia: Chronicle of state securitization measures. Journalism Research, 6(1), 71–92. https://doi.org/10.1453/2569-152x-12023-13030-en

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://research.fhstp.ac.at/projekte/anivision

de Jesus Oliveira, V. A., Slijepčević, D., Dumphart, B., Ferstl, S., Reis, J., Raberger, A.-M., Heller, M., Horsak, B., & Iber, M. (2023). Auditory feedback in tele-rehabilitation based on automated gait classification. Personal and Ubiquitous Computing. https://doi.org/10.1007/s00779-023-01723-2

Dumphart, B., Slijepcevic, D., Zeppelzauer, M., Kranzl, A., Unglaube, F., Baca, A., & Horsak, B. (2023). Robust deep learning-based gait event detection across various pathologies. PLOS ONE, 18(8), e0288555. https://doi.org/10.1371/journal.pone.0288555

Dumphart, B., Slijepcevic, D., Kranz, A., Zeppelzauer, M., & Horsak, B. (2023). Is it time to re-think the appropriateness of autocorrelation for gait event detection? Preliminary results of an ongoing study. Gait & Posture, 106, S50–S51. https://doi.org/10.1016/j.gaitpost.2023.07.064

Franziska, B. (2023, June 14). VRinMotion: Experimental Stop-Motion and Puppeteering in Virtual Environments [Vortrag]. Society for Animation Studies 34th Annual Conference – The Animated Environment, Online – Glassboro. https://research.fhstp.ac.at/projekte/vrinmotion

Ganahl, S. (2023). Foucault, the Digital Humanities, the Method. Genealogy+Critique, 9(1), 1–13. https://doi.org/10.16995/gc.10313

Horst, F., Slijepcevic, D., Simak, M., Horsak, B., Schöllhorn, W. I., & Zeppelzauer, M. (2023). Modeling biological individuality using machine learning: A study on human gait. Computational and Structural Biotechnology Journal, 21, 3414–3423. https://doi.org/10.1016/j.csbj.2023.06.009

Bibtex

Killian, S., Baumann, C., Delorette, M., Freisleben- Teutscher, C., Größbacher, S., Huber, A., Husinsky, M., Judmair, P., Moser, T., Pflegerl, J., Schlager, A., Schöffer, L., Taurer, F., & Vogt, G. (2023). MIRACLE - Mixed Reality und Cooperation im Lehreinsatz: Erfahrungen, Potenziale, Limitationen. In Lernen über den Tellerrand hinaus. Good Practices zu Interdisziplinarität, Internationalisierung und Future Skills (pp. 119–126). Lemberger Publishing.

Bibtex

Litschka, M. (2023). Classical Political Economy. In Handbook of Media and Communication Economics. Springer. https://doi.org/10.1007/978-3-658-34048-3_2-2

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

Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Explainable Machine Learning in Human Gait Analysis: A Study on Children With Cerebral Palsy. IEEE Access, 11, 65906–65923. https://doi.org/10.1109/ACCESS.2023.3289986

Slijepcevic, D., Horst, F., Simak, M., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2023). Towards personalized gait rehabilitation: How robustly can we identify personal gait signatures with machine learning? Gait & Posture, 106, S192–S193. https://doi.org/10.1016/j.gaitpost.2023.07.232

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

Ganahl, S., & Prager, K. (Eds.). (2022). Karl Kraus-Handbuch: Leben – Werk – Wirkung. Metzler. https://doi.org/10.1007/978-3-476-05804-1