Year 2023

• Road traffic can be predicted by machine learning equally effectively as by complex microscopic model

  Publication

  • A. Sroczyński
  • A. Czyżewski

  - Scientific Reports - Year 2023

  Since high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...

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Year 2021

• An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks

  Publication

  • M. Kurowski
  • A. Sroczyński
  • G. Bogdanis
  • A. Czyżewski

  - Electronics - Year 2021

  Handwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...

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Year 2018

• A Device for Measuring Auditory Brainstem Responses to Audio

  Publication

  • P. Odya
  • A. Czyżewski
  • A. Sroczyński
  • B. Kostek

  - Year 2018

  Standard ABR devices use clicks and tone bursts to assess subjects’ hearing in an objective way. A new device was developed that extends the functionality of a standard ABR audiometer by collecting and analyzing auditory brainstem responses (ABR). The developed accessory allows for the use of complex sounds (e.g., speech or music excerpts) as stimuli. Therefore, it is possible to find out how efficiently different types of sounds...

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