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[Finding suitable common feature sets for use in multiclass subject independent brain-computer interface (BCI) classifiers is problematic due to characteristically large inter-subject variation of electroencephalographic signatures. We propose a wrap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b3b4c257e6f11b6ed8c6bfab356906a
https://doi.org/10.1101/2020.02.07.938548
https://doi.org/10.1101/2020.02.07.938548
Autor:
Reza Derakhshani, Jesse Lowe
Publikováno v:
Image and Vision Computing. 107:104107
As a practical pursuit of quantified uniqueness, biometrics explores the parameters that make us who we are and provides the tools we need to secure the integrity of that identity. In our culture of constant connectivity, an increasing reliance on bi
Publikováno v:
BIBM
An electroencephalogram (EEG) is a recording of the brains electrical activity measured at the scalp. It is composed of multifaceted signals that reflect the localized activity and intensity of neurological processes opening the possibilities for bra
Publikováno v:
Acta Cytologica. 43:58-64
OBJECTIVE: To evaluate the AutoCyte Interactive Screening System (AutoCyte-Screen) as a prescreener for the cytologic detection of cervicovaginal abnormalities. STUDY DESIGN: Eight hundred fifty-six AutoCyte Preparation System from cervicovaginal sam
Publikováno v:
Acta cytologica. 42(1)
OBJECTIVE: To determine if thin-layer processing of cervicovaginal samples improves detection of cytologic abnormalities by reducing problems related to direct smear preparation. STUDY DESIGN: Eight hundred fifty-two cervical samples were collected a