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pro vyhledávání: '"Bedel, Hasan Atakan"'
Autor:
Bedel, Hasan Atakan, Çukur, Tolga
Deep learning analyses have offered sensitivity leaps in detection of cognitive states from functional MRI (fMRI) measurements across the brain. Yet, as deep models perform hierarchical nonlinear transformations on their input, interpreting the assoc
Externí odkaz:
http://arxiv.org/abs/2307.09547
Deep-learning models have enabled performance leaps in analysis of high-dimensional functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for contextual representations across diverse time scales. Here, we present BolT, a
Externí odkaz:
http://arxiv.org/abs/2205.11578
Akademický článek
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Publikováno v:
Signal Processing and Communications Applications Conference (SIU)
Conference Name: 2022 30th Signal Processing and Communications Applications Conference (SIU) Date of Conference: 15-18 May 2022 Functional magnetic resonance imaging (fMRI) enables recording the brain’s neural activity spatiotemporally and is the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a9fbe7a62efefe3363df06c7af9316e
https://hdl.handle.net/11693/111296
https://hdl.handle.net/11693/111296