#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

IMREA - Intelligente Multimodale Immobilienanalyse

Multimodale Informationsextraktions- und maschineller Lernverfahren zur Extraktion immobilienbezogener Attribute und Parameter aus heterogenen Eingabedaten

Plant Monitoring AI

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

Publikationen

Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breitender, C., Schöllhorn, W., & Zeppelzauer, M. (2022). Explaining Machine Learning Models for Clinical Gait Analysis. ACM Transactions on Computing for Healthcare, 3(2), 14:1–14:27. https://doi.org/10/gnt2s9
Horsak, B., Simonlehner, M., Schöffer, L., Dumphart, B., Jalaeefar, A., & Husinsky, M. (2021). Overground walking in a fully immersive Virtual Reality: Preliminary results of a comprehensive study on the effects on walking biomechanics. Gait & Posture, 90, 100–101. https://doi.org/https://doi.org/10.3389/fbioe.2021.780314
Krondorfer, P., Slijepčević, D., Unglaube, F., Kranzl, A., Breiteneder, C., Zeppelzauer, M., & Horsak, B. (2021). Deep learning-based similarity retrieval in clinical 3D gait analysis. Gait & Posture, 90, 127–128. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.066
Horst, F., Slijepcevic, D., Simak, M., & Schöllhorn, W. I. (2021). Gutenberg Gait Database, a ground reaction force database of level overground walking in healthy individuals. Scientific Data, 8(1), 232. https://doi.org/https://doi.org/10.1038/s41597-021-01014-6
Koch, D., Despotovic, M., Thaler, S., & Zeppelzauer, M. (2021). Where do University Graduates live? – A Computer Vision Approach using Satellite Images. Applied Intelligence, 51, 8088–8105. https://doi.org/https://doi.org/10.1007/s10489-021-02268-8
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2021). A Taxonomy of Property Measures to Unify Active Learning and Human-centered Approaches to Data Labeling. ACM Transactions on Interactive Intelligent Systems (TiiS), 11(3–4), 1–42. https://doi.org/10/gnt2wf
Koch, D., Despotovic, M., Sascha, L., Sakeena, M., Döller, M., & Zeppelzauer, M. (2020). Real Estate Image Analysis - A Literature Review. Journal of Real Estate Literature, 27(2), 269–300. https://doi.org/10/gnt2wg
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/gnkdht
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/gh372d
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/10/ghz24x

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