#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.

Projekte

Plant Monitoring AI

Maschinelles lernen und automatische Vorhersagemodelle zur Früherkennung von Pflanzenstress für eine höhere Nachhaltigkeit in der Landwirtschaft

Active deep learning for object detection

Entwicklung neuer Strategien zur Integration von Active Learning und Deep Learning für den Einsatz künstlicher Intelligenz

Publikationen

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, 81, 159–160. https://doi.org/10.1016/j.gaitpost.2020.07.114
Koch, D., Despotovic, M., Döller, M., Leiber, S., & Zeppelzauer, M. (2020). Computer Vision in Building Research: An Application for Prediction of Condition and Costs of a Property. Building Research & Information, Submitted.
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, 7:143(1), 1–8. https://doi.org/10.1038/s41597-020-0481-z
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2020). A Taxonomy of Property Measures to Unify Active Learning and Human-Centered Approaches To Data Labeling. ACM Transactions on Interactive Intelligent Systems (TiiS), to appear.
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. Eurovis 2020, Norrköping, Sweden.
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., 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.
Slijepcevic, D., Raberger, A.-M., Zeppelzauer, M., Dumphart, B., Breiteneder, C., & Horsak, B. (2019). On the usefullness of statistical parameter mapping for feature selection in automated gait classification. Book of Abstracts of the 25th Conference of the European Society of Biomechanics (ESB), 1.

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