ZBUM - Biometrics and Machine Learning Group Site - Biometrics and Machine Learning Group

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    • M. Trokielewicz
    • E. Bartuzi
    • M. Hałoń
    • K. Roszczewska
    • A. Dzieniszewska
    • W. Gutfeter
    • K. Gabor
    • M. Azimi
    • J. N. Khirak
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Biometrics and Machine Learning Group

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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.

wersja polska

Computer Vision (CSE 40535/60535)

back to Computer Vision (CSE 40535/60535)

Practicals

1. Detection of color objects in live stream

This practical session will demon- strate how to process live webcam stream, detect color objects and track them (Python codes).

2. Object classification

This practical session will demonstrate how to automat- ically estimate simple geometrical features of objects and classify these objects (Matlab codes and instructions).

3. Image stitching

This practical session will show the difference between forward and inverse warping. We will use inverse warping in image stitching (Matlab codes and instructions).

4. CNN-based object recognition

This practical session will demonstrate how to use pre-trained convolutional neural networks in feature extraction and image recognition (Python codes and instructions).

Contact us

Institute of Control
and Computation Engineering

Warsaw University of Technology
ul. Nowowiejska 15/19
00-665 Warsaw, Poland
phone: +48 (22) 234 73 97

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