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Matthias
Zeppelzauer
Mag. Dipl.Ing. Dr.

Matthias Zeppelzauer is data science and pattern recognition researcher and works as a senior researcher at the Institute of Creative Media Technologies at St. Poelten University of Applied Sciences, since 2013.

From 2011 to 2015, he worked as a postdoctoral researcher at the Interactive Media Systems Group at the Vienna University of Technology in the areas of content-based audio and visual retrieval, computer vision, and machine learning. He graduated with Master of Sciences at Vienna University of Technology in Computer Science and Business Informatics in 2005 and 2006, respectively, and holds a PhD in Computer Science from the Vienna University of Technology. Matthias Zeppelzauer is involved in the acquisition and execution of a numerous basic and applied research projects at national and international levels. He is a lecturer for undergraduate- and graduate programs with an emphasis on signal processing and content-based retrieval. Matthias Zeppelzauer received several performance scholarships from the Vienna University of Technology and was awarded by the Austrian Computer Society for outstanding achievements in the area of pattern recognition.


Research Interests: pattern recognition · computer vision · machine learning · deep learning · data mining · multimodal retrieval· social media analysis

Activities:



Recent Publications

Slijepcevic, D., M. Zeppelzauer, A-M. Raberger, C. Schwab, M. Schüller, A. Baca, and C. Breiteneder, "Automatic Classification of Functional Gait Disorders", IEEE Journal of Biomedical and Health Informatics, Submitted.
Slijepcevic, D., Brian Horsak, C. Schwab, A-M. Raberger, M. Schüller, A. Baca, C. Breiteneder, and M. Zeppelzauer, "Ground reaction force measurements for gait classification tasks: Effects of different PCA-based representations", Gait & Posture, vol. 57, pp. 4-5, 08/2017.
Despotivic, M., M. Sakeena, D. Koch, M. Döller, and M. Zeppelzauer, "Predicting Heating Energy Demand by Computer Vision", Computer Science - Research and Development, 2017.
Bernard, J., M. Zeppelzauer, M. Sedlmair, and W. Aigner, "Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study", IEEE Transactions on Visualization and Computer Graphics (TVCG), 2017.
Poier, G., M. Seidl, M. Zeppelzauer, C. Reinbacher, M. Schaich, G. Bellandi, A. Marretta, and H. Bischof, "The 3D-Pitoti Dataset: A Dataset for high-resolution 3D Surface Segmentation", Content Based Multimedia Indexing, Special Session on Multimedia for Cultural Heritage, Florence, pp. 8, 06/2017.

Press articles