#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

Applied Biomechanics in Rehabilitation Research

Endowed professorship of the province of Lower Austria to strengthen and expand the research focus on motor rehabilitation

SBA Research

K1 competence center for Information Security

Scribe ID AI

Active Machine Learning for automatic identification of handwriting in 12th century manuscripts

Plant Monitoring AI

Leveraging machine learning and predictive analytics for early detection of plant stress for the benefit of sustainability in farming

Active deep learning for object detection

Developing novel strategies for integrating Active and Deep Learning for Artificial Intelligence

LINK

Analysis and nowcasting of extreme weather events using data from radio links

Digital Makers Hub

Platform for digital makers, for interaction, efficient sharing of knowledge & experiences and nationwide coordination of activities

DIHOST - Digital Innovation Hub Lower Austria/Vienna/Burgenland

Comprehensive service programme to increase the transformation capacity and transformation speed of SMEs in Eastern Austria with regard to digital innovations

IntelliGait 3D- Gait Data Mining

Establishing advanced analysis methods for modelling, classification and similarity retrieval of gait patterns to enable novel data-driven ways to access 3D gait databases

Smart Companion

Using everyday low-cost robot sensors and smart speech recognition in assistance services for elderly people

Publications

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
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
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
Horsak, B., Schwab, C., Leboeuf, F., & Kranzl, A. (2020). Reliability of walking and stair climbing kinematics in a young obese population using a standard kinematic and the CGM2 model. Gait & Posture. https://doi.org/10.1016/j.gaitpost.2020.10.017
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.
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.
Eresheim, S. (2020). Reinforcement Learning for Incident Protection in IT. First Conference on Mathematics of Data Science (MDS20).
Eresheim, S. (2020). Cybersecurity Containment Agent. Machine Learning Prague 2020.

News

11/24/2020

Digital Makers Hub Celebrates First Anniversary

08/25/2020

CD-MAKE 2020 Proceedings available

08/07/2020

Successful Research for Medicine

Blog posts

Video zu Science at Home-Event

Andreas Gebesmair hat für das Science at Home-Event ein Präsentations-Video zu SAMBA erstellt, welches live am 8.5.2020 präsentiert wurde.

https://scienceathome.fhstp.ac.at/scientistshome/