Dr. Thomas Hoch
S. Vora, M. Shahriari Shourabi, S. Thomopoulos, L. Fischer, T. Hoch. A scoring algorithm for abnormal passenger behavior in border-crossing areas. In H. Bouma, R. Prabhu, R. Stokes, Y. Yitzhaky (editors), Proceedings SPIE, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV, volume 11542, pages 1154206, DOI 10.1117/12.2573963, October, 2020.
A. Kuhn, J. Carmona, A. Schirrer, S. Jakubek, T. Hoch, K. Pollhammer, K. Hirschmann-Kraschl, W. Schildorfer. Scenario based approach in Connecting Austria for the development and validation of connect, cooperative, (semi-)automated driving in the case of intersections. TRA 2020: Proceedings of the 8th Transport Research Arena, pages 200-201, Finnish Transport and Communications Agency Traficom, May, 2020.
H. Eghbal-zadeh, L. Fischer, T. Hoch. On conditioning GANs to hierarchical ontologies. In G. Anderst-Kotsis, A. Tjoa, I. Khalil, E. al. (editors), Database and Expert Systems Applications - Proc DEXA 209 International Workshops, Communications in Computer and Information Science, volume 1062, pages 182-186, DOI 10.1007/978-3-030-27684-3_23, Springer, August, 2019.
R. Leser, T. Hoch, X. Tan, B. Moser, G. Kellermayr, A. Baca. Finding efficient strategies in 3-versus-2 soccer small-sided games of youth soccer players. Kinesiology: International journal of fundamental and applied kinesiology, volume 51, number 1, pages https://hrcak.srce.hr/203816, July, 2018.
N. Shepeleva, T. Hoch, L. Fischer, W. Kloihofer, B. Moser. Removing nuisance in tracklet data. In H. Bouma, R. Prabhu, R. Stokes, Y. Yitzjaky (editors), Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies II - Proc. SPIE 2018, volume 10802, pages 08020S, DOI 10.1117/12.2325636, SPIE, November, 2018.
T. Hoch, X. Tan, R. Leser, A. Baca, B. Moser. A knowledge discovery framework for the assessment of tactical behaviour in soccer based on spatiotemporal data. Mathematical and Computer Modelling of Dynamical Systems, volume 23, number 4, pages 384-398, DOI: 10.1080/13873954.2017.1336634, June, 2017.
T. Hoch. An ensemble learning approach for the kaggle taxi travel time prediction challenge. In A. Martínez-Usó, J. Mendes-Moreira, L. Moreira-Matias, M. Kull, N. Lachiche (editors), Proceedings of the ECML/PKDD 2015 Discovery Challenges, CEUR Workshop Proceedings, volume 1526, pages http://ceur-ws.org/Vol-1526/paper22.pdf, CEUR, January, 2016.
T. Hoch, R. Leser, X. Tan, A. Baca, B. Moser. Identifying tactical patterns in soccer game play by means of an explanatory computational model. Book of Abstracts of the 21st annual Congress of the European College of Sport Science (ECSS 2016), pages 548, July, 2016.
R. Leser, T. Hoch, X. Tan, B. Moser, A. Baca. Searching tactical patterns in soccer game play by unsupervised machine learning. volume Book of Abstracts of the 21st annual Congress of the European College of Sport Science (ECSS 2016), pages 548, July, 2016.
T. Hoch, M. Dorfer, C. Helmbrecht. Subpixel localisation of nanoparticles in image sequences. In K. Niel, P. Roth, M. Vincze (editors), Proceedings of the 1st OAGM-ARM Joint Workshop Vision Meets Robotics, pages 61, May, 2016.
T. Hoch, X. Tan, R. Leser, A. Baca, B. Moser. Towards data-based assessment of individual tactics skills in team sports based on fuzzy petri nets. Technical Report, number SCCH-TR-16022, December, 2016.
R. Leser, T. Hoch, B. Moser, A. Baca. Expert oriented analysis of football duels by means of position data. In J. Bangsbo, P. Krustrup (editors), Book of Abstracts of the 8th World Congress on Science and Football (WCSF 2015), pages 65, May, 2015.
R. Leser, B. Moser, T. Hoch, J. Stöger, G. Kellermayr, S. Reinsch, A. Baca. Expert-oriented modelling of a 1vs1-situation in football. International Journal of Performance Analysis in Sport, volume 15, number 3, pages 949-966, December, 2015.
T. Hoch, M. Dorfer, R. Leser, G. Stelzhammer, A. Baca. Kamerabasierte Bestimmung der Puck-Position im Eishockey. Sportinformatik X, Schriften der Deutschen Vereinigung für Sportwissenschaft, volume 244, pages 36-41, Feldhaus, June, 2015.
A. Golabgir, T. Hoch, M. Zharyi, C. Herwig. Observability analysis of biochemical process model as a valuable tool for the development of mechanistic soft-sensors. Biotechnology Progress, volume 31, number 6, pages 1703-1715, DOI: 10.1002/btpr.2176, November, 2015.
A. Serafini, R. Leser, T. Hoch, B. Moser, A. Baca. Towards data-based assessment of individual tactics skills in team sports based on Fuzzy Petri Nets. In F. Breitenecker, A. Kugi, I. Troch (editors), Abstract volume of the 8th Vienna International Conference on Mathematical Modelling - MATHMOD 2015, Argesim Report No. 44, pages 303-304, ARGESIM, February, 2015.
R. Leser, B. Moser, T. Hoch, O. Drachta, G. Stelzhammer, A. Baca. Wissensbasierte Modellierung der individuellen Spielleistung von LeistungssportlerInnen in Mannschaftsportarten. Sportinformatik X, Schriften der Deutschen Vereinigung für Sportwissenschaft, volume 244, pages 125-129, Feldhaus, June, 2015.
B. Moser, T. Hoch. Misalignment measure based on Hermann Weyl's. In A. Kuijper, B. Heise, L. Muresan (editors), Proceedings of 32nd Workshop of the Austrian Association for Pattern Recogntion (AAPT/OAGM), Challenges in the Biosciences: Image Analysis and Pattern Recognition Aspects, pages 187-198, OCG, May, 2008.
Dr. Thomas Hoch is a Senior Researcher and Project Leader in the Knowledge-Based Vision Systems for Industrial Applications Group at the Software Competence Center Hagenberg. He received his Diploma in Computer Science in 2001 and his PhD degree in 2006 both from the Technical University of Berlin in the Area of Neural Information Processing. He won on Kaggle an international Data Mining competition about taxi travel time prediction held by ECML/PKDD conference in 2015.
Dr. Thomas Hoch has been engaged in the COMET research project on multi camera based tracking in soccer and ice hockey from the very beginning since 2006 as project manager and key researcher. Along with this long-standing multi-camera tracking research project, Dr. Hoch, intimately familiar with the underlying technology and the resulting data, developed himself to an expert for spatio-temporal data analysis. In the FFG research project WiMoiS as well as SKIN (KIRAS) he is the principal investigator with focus on the spatial analysis of time dependent position data by means of deep learning and unsupervised clustering techniques.