Csaba BENEDEK

Csaba BENEDEK

Biography

Csaba Benedek (PhD, DSc, dr. habil) is full professor with the Faculty of Information Technology and Bionics of the Péter Pázmány Catholic University, Budapest, where he is the lecturer of the Basic Image Processing and Computer Graphics courses, and he supervises several undergraduate and PhD students in topics related to computer vision and machine perception. He is also a deputy director of the Institute for Computer Science and Control (SZTAKI) and works as a scientific advisor in the Machine Perception Research Laboratory of SZTAKI, where he is the head of the Research Group on Geo-Information Computing. 

Prof. Benedek is a governing board member of the International Association for Pattern Recognition (IAPR), a vice chairman of the John von Neumann Computer Society, the oldest IT society in Hungary, and a former president of the Hungarian Image Processing and Pattern Recognition Society (Képaf). He is a Senior Member of IEEE, and an editorial board member of Elsevier’s Digital Signal Processing journal. He received various awards including the Bolyai plaquette from the Hungarian Academy of Sciences (HAS) 2019, Imreh Csanád plaquette (2019) and master teacher gold medal (2023) from the National Council of Student Research Societies, and the Michelberger Master Award from the Hungarian Academy of Engineering (2020). He has been the manager of various national and international research projects in the recent years funded by the Hungarian Research Fund (OTKA), European Space Agency (ESA), European Defense Agency (EDA), EUREKA etc. His research interests include Bayesian image and point cloud segmentation, object extraction, change detection, machine learning applications and GIS data analysis. 

Publications

  • • Cs. Benedek: ”Multi-level Bayesian Models for Environment Perception,” Springer International Publishing, 202 pages, ISBN 978-3-030-83654-2, 2022
  • • Y. Ibrahim and Cs. Benedek: ”MVPCC-Net: Multi-View Based Point Cloud Completion Network for MLS Data,” Image and Vision Computing, Elsevier, vol. 134, article 104675, 2023
  • • Ö. Zováthi, B. Pálffy, Zs. Jankó and Cs. Benedek: ”ST-DepthNet: A spatio-temporal deep network for depth completion using a single non-repetitive circular scanning Lidar,” IEEE Robotics and Automation Letters, vol. 8, no. 6, pp. 3270-3277, 2023
  • • Ö. Zováthi, B. Nagy and Cs. Benedek: ”Point Cloud Registration and Change Detection in Urban Environment Using an Onboard Lidar Sensor and MLS Reference Data,” International Journal of Applied Earth Observation and Geoinformation, Elsevier, vol. 110, article 102767, 2022
  • • Cs. Benedek, B. Gálai, B. Nagy and Z. Jankó: ”Lidar-based Gait Analysis and Activity Recognition in a 4D Surveillance System,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 28, no. 1, pp. 101-113, 2018
  • • Cs. Benedek: "An Embedded Marked Point Process Framework for Three-Level Object Population Analysis", IEEE Trans. on Image Processing, vol. 26, no. 9, pp. 4430-4445, 2017
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