#Data Science
Mit Data Science lassen sich brauchbare Informationen in großen Mengen komplexer Daten entdecken, analysieren und visualisieren.
Publikationen
Horsak, B., Simonlehner, M., Schöffer, L., Maureder, J., Schwab, C., Raberger, A. M., Zeller, M., & Husinsky, M. (2020). Applicability and usability of an immersive virtual reality-based balance control exergame for prosthetic users: A pilot study with healthy individuals. Gait & Posture. ESMAC 29th Annual Meeting, Virtual Meeting. https://doi.org/10.1016/j.gaitpost.2020.07.113
Koch, D., Despotovic, M., Thaler, S., & Zeppelzauer, M. (2020). Estimating Graduate Density in Satellite Images - A Machine Learning Approach. Elsevier Computers, Environment and Urban Systems, Submitted.
Oliveira, V. A. D. J., Stoiber, C., Grüblbauer, J., Musik, C., Ringot, A., & Gebesmair, A. (2020). SAMBAVis: Design Study of a Visual Analytics Tool for the Music Industry Powered by YouTube Comments. 5.
Horsak, B., Slijepcevic, D., Raberger, A.-M., Schwab, C., Worisch, M., & Zeppelzauer, M. (2020). GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait. Scientific Data, 7(1), 143. https://doi.org/10.1038/s41597-020-0481-z
Horst, F., Slijepcevic, D., Zeppelzauer, M., Raberger, A. M., Lapuschkin, S., Samek, W., Schöllhorn, W. I., Breiteneder, C., & Horsak, B. (2020). Explaining automated gender classification of human gait. Gait & Posture. ESMAC 29th Annual Meeting, Virtual Meeting. https://doi.org/10.1016/j.gaitpost.2020.07.114
Slijepcevic, D., Zeppelzauer, M., Schwab, Caterine, Raberger, A.-M., Breitender, C., & Horsak, B. (2020). Input Representations and Classification Strategies for Automated Human Gait Analysis. Gait & Posture, 76, 198–203. https://doi.org/https://doi.org/10.1016/j.gaitpost.2019.10.021
Horsak, B., Dumphart, B., Slijepcevic, D., & Zeppelzauer, M. (2020). Explainable Artificial Intelligence (XAI) und ihre Anwendung auf Klassifikationsprobleme in der Ganganalyse. Abstractband Des 3. GAMMA Kongress. 3. GAMMA Kongress, München, Deutschland.
Eresheim, S. (2020). Reinforcement Learning for Incident Protection in IT. First Conference on Mathematics of Data Science (MDS20).
Luh, R., & Schrittwieser, S. (2019). Advanced threat intelligence: detection and classification of anomalous behavior in system processes. E \& i Elektrotechnik Und Informationstechnik, Springer, 1–7.