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The 3rd international workshop on Machine Learning for EEG Signal Processing

6-9 déc. 2022
Las Vegas, NV, USA - Las Vegas (États-Unis)

http://mlesp2022.sciencesconf.org

The 3rd international workshop on Machine Learning for EEG Signal Processing (MLESP 2022) to be held in Las Vegas, USA, from 6 to 9 december 2022, in conjunction with the IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2022). Overview EEG signal processing involves the analysis and treatment of the electrical activity of the brain measured with Electroencephalography, or EEG, in order to provide useful information on which decisions can be made. The recent advances in signal processing and machine learning for EEG data processing have brought an impressive progress to solve several practical and challenging problems in many areas such as healthcare, biomedicine, biomedical engineering, BCI and biometrics. The aim of this workshop is to present and discuss the recent advances in machine learning for EEG signal analysis and processing. We are inviting original research work, as well as significant work-in-progress, covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in EEG data analytics. This workshop is an opportunity to bring together academic and industrial scientists to discuss the recent advances. The topics of interest include but not limited to: - EEG signal processing and analysis - Time-frequency EEG signal analysis - Signal processing for EEG Data - EEG feature extraction and selection - Machine learning for EEG signal processing - EEG classification and Hierarchical clustering - EEG abnormalities detection (e.g. Epileptic seizure, Alzheimer's disease, etc.) - Machine learning in EEG Big Data - Deep Learning for EEG Big Data - Neural Rehabilitation Engineering - Brain-Computer Interface - Neurofeedback - EEG-based Biometrics - Related applications
Discipline scientifique : Informatique - Intelligence artificielle - Apprentissage - Traitement du signal et de l'image

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