Wykaz obszarów badawczych związanych z tagiem Uczenie-glebokie:
| # | Obszar badawczy | Dziedzina naukowa |
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| 1 |
The research area covers the issues of image processing, computer vision, machine learning (including deep learning) and broadly understood artificial intelligence.
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| 2 |
The research topic includes the development of algorithms for the processing and analysis of physiological signals, including EEG, for the purpose of the detection and prediction of epileptic seizures. The research will also cover the location of the sources of epilepsy. An important aspect of the research will be the development of algorithms that can be used in medical practice. The EEG signals database collected as part of cooperation with the Medical University of Warsaw for over 50 people is available for use. The pre-processing research is expected to develop an EMG / EEA / ECG artifact elimination method. The task involves the development of effective trait extraction methods for the detection and prediction of epileptic seizures. As an important research novelty, it is worth considering the use of deep learning, including autoencoders and convolutional neural networks.
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| 3 |
Speech signal analysis to detect the emotional state of the speaker.
The research task includes a comprehensive speech signal analysis to identify the speaker's emotional state. Data processing algorithms include analyzing static and dynamic signal features and selecting the best ones. Machine learning algorithms, including deep learning, will be used to determine the speaker's emotional state.
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| 4 |
Analysis of physiological signals to detect fatigue.
The research task requires developing and constructing a test stand that enables the acquisition of various physiological signals at different stages of user fatigue. It is planned to use the following signals: electroencephalographic (EEG), electrooculographic (EOG), and audio-visual. In the next step, methods of analyzing the acquired signals in terms of fatigue detection should be developed. Data processing algorithms include feature extraction, feature selection, and machine learning (also deep learning).
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