Biometrics and Machine Learning Group
Latest news
February 2025: conference proceedings - Rasel Ahmed Bhuiyan, Mateusz Trokielewicz, Piotr Maciejewicz, Sherri Bucher, Adam Czajka. "Iris Recognition for Infants" Proceedings of the Winter Conference on Applications of Computer Vision (WACV) Workshops, February 2025, pp. 83-92.
December 2024: journal papers - Mateusz Trokielewicz, Piotr Maciejewicz, Adam Czajka. "Post-mortem iris biometrics – Field, applications and methods." Forensic Science International, Volume 365, 2024, Article 112293. ISSN 0379-0738. https://doi.org/10.1016/j .forsciint.2024.112293.
April 2024: journal papers - Adrian Kordas, Ewelina Bartuzi-Trokielewicz, Michał Ołowski, Mateusz Trokielewicz, "Synthetic Iris Images: A Comparative Analysis between Cartesian and Polar Representation" 2024, Sensors, 24(7), 2269, https://doi.org/10.3390/ s24072269
We are pleased to announce that Weronika Gutfeter defended her doctoral dissertation on face recognition based on multi-shot images using deep aggregation networks, supervised by prof. Andrzej Pacut, on the 18th of May, 2023.
Who We Are
Biometrics and Machine Learning Group (ZBUM) is a part of the Institute of Control and Computation Engineering at the Faculty of Electronics and Information Technology of the Warsaw University of Technology.
Area of interest
The research is centered on biologically inspired control and information technology, including biometrics, machine learning, uncertainty modeling, and biological modeling. Biometrics consists in using personal characteristics for identity authentication. Our research in biometrics includes pattern recognition for iris, hand-written signature, face image, etc. Also, safety of biometric data storage and exchange, biometrics intelligent cards, and data encryption using biometrics are investigated. Machine learning research is focused on reinforcement learning, applied to adaptive control, and multi-agent systems. Also, learning in neural networks and modeling granularity is investigated.