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pro vyhledávání: '"Lies Bollens"'
Autor:
Mohammad Jalilpour Monesi, Lies Bollens, Bernd Accou, Jonas Vanthornhout, Hugo Van Hamme, Tom Francart
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 652-661 (2024)
This paper describes the auditory EEG challenge, organized as one of the Signal Processing Grand Challenges at ICASSP 2023. The challenge provides EEG recordings of 85 subjects who listened to continuous speech, as audiobooks or podcasts, while their
Externí odkaz:
https://doaj.org/article/896e855ee0ce47a1badb14a75bccdba5
Publikováno v:
Data, Vol 9, Iss 8, p 94 (2024)
Researchers investigating the neural mechanisms underlying speech perception often employ electroencephalography (EEG) to record brain activity while participants listen to spoken language. The high temporal resolution of EEG enables the study of neu
Externí odkaz:
https://doaj.org/article/ca973a938f964fca960cdfebf421f83d
The electroencephalogram (EEG) is a powerful method to understand how the brain processes speech. Linear models have recently been replaced for this purpose with deep neural networks and yield promising results. In related EEG classification fields,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8572c6f160e403d7359adccdb45e4f9
Publikováno v:
ICIP
This paper focuses on the problem of unsupervised image-to-image translation. More specifically, we aim at finding a translation network such that objects and shapes that only appear in the source domain are translated to objects and shapes only appe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c66f1d219e11ccbbbc40d89133952ed8
https://lirias.kuleuven.be/handle/123456789/641904
https://lirias.kuleuven.be/handle/123456789/641904