Sep 24, 2015 · In this paper, we focus on the permanence across time of brain signals, specifically of electroencephalographic (EEG) signals, issue of ...
On the Permanence of EEG Signals for Biometric Recognition
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The aim of this paper is intended to stimulate research on the use of light and portable EEG headset configurations by adopting network-based representations of ...
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Abstract—Brain signals have been investigated for more than a century in the medical field. However, despite the broad interest.
Jan 1, 2016 · In this paper, we focus on the permanence across time of brain signals, specifically of electroencephalographic (EEG) signals, issue of ...
An extensive set of experimental tests on the permanence across time of brain signals, specifically of electroencephalographic (EEG) signals, issue of ...
Sep 24, 2021 · The results indicated that the EEG-FC networks are quite subject-specific with a high-precision identification accuracy of greater than 90%.
A biometric recognition framework that increases EEG channel density improves recognition accuracy and stability. •. Deep neural networks learn effective ...
Duration: 9:21
Posted: Apr 7, 2017
Posted: Apr 7, 2017
Dec 6, 2022 · In this paper, we explore the use of state-of-the-art DL models such as ResNet, Inception, and EEGNet to realize EEG-based biometrics on the BED ...
On the Permanence of EEG Signals for Biometric Recognition
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In this paper, we focus on the permanence across time of brain signals, specifically of electroencephalographic (EEG) signals, issue of paramount importance for ...