#Artificial Intelligence
Mit künstlicher Intelligenz lernen Maschinen und Programme aus Erfahrung, reagieren auf neue, unvorhergesehen Situationen und können ähnlich wie Menschen komplexe Aufgaben bewältigen und Informationen in größere Zusammenhänge einordnen.
Publikationen
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
Franziska, B., Erwin, F., & Patrik, L. (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/
Erwin, F. (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/
Erwin, F. (2023, August 6). Projektvorstellung AniVision [Vortrag]. Tools und Plattformen in der Praxis – Workshop der DHd AG Film und Video, Online. https://dhdagfilm.hypotheses.org/
Erwin, F. (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
Erwin, F. (2022, February 10). Writing the Histories of Animation in the Time of Artificial Intelligence [Vortrag]. StopTrik Festival, Maribor. https://www.stoptrik.com/
Slijepcevic, D., Horst, F., Simak, M., Lapuschkin, S., Raberger, A. M., Samek, W., Breiteneder, C., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2022). Explaining machine learning models for age classification in human gait analysis. Gait & Posture, 97, S252–S253. https://doi.org/10.1016/j.gaitpost.2022.07.153
Rind, A., Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., & Horsak, B. (2022). Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy. Proc. 2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX), 7–15. https://doi.org/10.1109/TREX57753.2022.00006
Strebl, J., Stumpe, E., Baumhauer, T., Kernstock, L., Seidl, M., & Zeppelzauer, M. (2022). One-Pixel Instance Segmentation of Leaves. Proceedings of the Workshop of the Austrian Association for Pattern Recognition, 6.