Using autoencoders to denoise cross-session non-stationarity in EEG-based motor-imagery brain-computer interfaces

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Title	Using autoencoders to denoise cross-session non-stationarity in EEG-based motor-imagery brain-computer interfaces. textový dokument (print)
Author	Almagor O.
Co-authors	Avin O.
	Rosipal Roman 1969 SAVMER - Ústav merania SAV ^SCOPUS ^RID ^ORCID
	Shriki O.

Source document	2022 IEEE 16th International Scientific Conference on Informatics. P. 24-28. - : IEEE, 2022 / Steingartner W. ; Korečko Š. ; Szakál A. ; INFORMATICS 2022 16th International Scientific Conference on Informatics
Language	eng - English
Country	US - United States of America
Document kind	rozpis článkov z periodík (rzb)
Citations	LIONAKIS, E. - KARAMPIDIS, K. - PAPADOURAKIS, G. Current Trends, Challenges, and Future Research Directions of Hybrid and Deep Learning Techniques for Motor Imagery Brain-Computer Interface. In MULTIMODAL TECHNOLOGIES AND INTERACTION. OCT 2023, vol. 7, no. 10. Dostupné na: https://doi.org/10.3390/mti7100095.
	VOSTINáR, P. - SROBáR, M. Creating computer games that are controlled by EEG helmets. In IPSI BGD TRANSACTIONS ON INTERNET RESEARCH. ISSN 1820-4503, JAN 2023, vol. 19, no. 1, SI, p. 59-65.
Category	ADMB - Scientific papers in foreign non-impacted journals registered in Web of Sciences or Scopus
Category of document (from 2022)	O2 - Odborný výstup publikačnej činnosti ako časť knižnej publikácie alebo zborníka
Type of document	príspevok z podujatia
Year	2023
Registered in	SCOPUS
DOI	10.1109/Informatics57926.2022.10083486

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	Using autoencoders to denoise cross-session non-stationarity in EEG-based motor-imagery brain-computer interfaces.pdf	Neprístupný/archív	390.4 KB	2	Publisher's version

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2022

Number of the records: 1