Year 2023

• Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation

  Publication

  • K. Ledwosiński
  • P. Czapla
  • T. Kocejko
  • J. Kang-Hyun

  - Year 2023

  Machine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...

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• Bimodal Emotion Recognition Based on Vocal and Facial Features

  Publication

  • M. Woźniak
  • M. Sakowicz
  • K. Ledwosiński
  • J. Rzepkowski
  • P. Czapla
  • S. Zaporowski

  - Year 2023

  Emotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions...

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