Artificial intelligence, data processing and analysis

Main research areas

  • Machine learning (research of new algorithms for machine learning and artificial intelligence)
  • Big data (parallel and distributed algorithms for processing of large volumes of data)
  • Computer vision (image content analysis, object detection and classification, object tracing, segmentation)
  • Biomedicine (applications for e-health and telemedicine)
  • Biometrics and anonymization (identification and verification of persons based on face recognition, advanced anonymization of faces, extraction of secondary biometric and non-biometric features - age, gender, etc.)
  • 3D audio

Laboratory equipment

  • Supercomputer equipped with several high-performance computing cards for acceleration of artificial intelligence calculations
  • Microscope for mineral analysis
  • Robotic arm

Partners

  • Companies: Kriminalistický ústav v Praze, Yunex Traffic, AT&T,  AŽD Praha s.r.o., ČEPS, Honeywell, JIMI CZ a.s., Konica-Minolta, Tokoz a.s.

Main practical research results

  • System for defectoscopy of painted metal parts
  • Artificial intelligence for categorizing ink spectra and one of the world's largest ink databases. The software enables efficient searches with the help of artificial intelligence. The tool was developed in collaboration with the Institute of Criminalistics in Prague
  • Intelligent traffic routing system
  • TOKOZ ePRO Information system
  • SP Analyzer - software tool for classification and segmentation of soil (mineral) phases for further comparative analysis. The tool was developed in cooperation with the Institute of Criminalistics in Prague.
  • Method of detecting attempts to unauthorized entry into protected areas (patent)
  • Surveillance system interface with automatic analysis of audiovisual content
  • Intelligent access and attendance system
  • Intelligent monitoring tool

Main research publications

Mezina, A., Genzor, S., Burget, R., Myska, V., Mizera, J. and Ometov, A., 2024. Corticosteroid treatment prediction using chest X-ray and clinical data. Computational and structural biotechnology journal, 24, pp.53-65.

Mizera, J., Genzor, S., Sova, M., Stanke, L., Burget, R., Jakubec, P., Vykopal, M., Pobeha, P. and Zapletalová, J., 2024. The effectiveness of glucocorticoid treatment in post-COVID-19 pulmonary involvement. Pneumonia, 16(1), p.2.

Sengar, N., Burget, R. and Dutta, M.K., 2022. A vision transformer based approach for analysis of plasmodium vivax life cycle for malaria prediction using thin blood smear microscopic images. Computer Methods and Programs in Biomedicine, 224, p.106996.

Khan, J.S., Kaushik, M., Chaurasia, A., Dutta, M.K. and Burget, R., 2022. Cardi-Net: A deep neural network for classification of cardiac disease using phonocardiogram signal. Computer Methods and Programs in Biomedicine, 219, p.106727.

Mezina, A., Burget, R. and Ometov, A., 2024. Reinterpreting Usability of Semantic Segmentation Approach for Darknet Traffic Analysis. Computer Networks, 249, p.110493.

V. Myska, R. Burget, M. Kolarik, V. Levek, P. Steffan and J. Haze, "IoT Mechatronic Access Control System ePRO 1.4," in IEEE Consumer Electronics Magazine, vol. 13, no. 5, pp. 83-92, Sept. 2024, doi: 10.1109/MCE.2023.3331169.