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[HTML][HTML] Representation learning and pattern recognition in cognitive biometrics: a survey
Cognitive biometrics is an emerging branch of biometric technology. Recent research has
demonstrated great potential for using cognitive biometrics in versatile applications …
demonstrated great potential for using cognitive biometrics in versatile applications …
Affective EEG-based person identification using the deep learning approach
T Wilaiprasitporn, A Ditthapron… - … on Cognitive and …, 2019 - ieeexplore.ieee.org
Electroencephalography (EEG) is another method for performing person identification (PI).
Due to the nature of the EEG signals, EEG-based PI is typically done while a person is …
Due to the nature of the EEG signals, EEG-based PI is typically done while a person is …
An overview of brain fingerprint identification based on various neuroimaging technologies
S Zhang, W Yang, H Mou, Z Pei, F Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As a novel category of biometric features, research on brain fingerprints has become a hot
topic in neuroscience, not only for its reliable performance on individual identification but …
topic in neuroscience, not only for its reliable performance on individual identification but …
Convolutional neural networks using dynamic functional connectivity for EEG-based person identification in diverse human states
Highly secure access control requires Swiss-cheese-type multi-layer security protocols. The
use of electroencephalogram (EEG) to provide cognitive indicators for human workload and …
use of electroencephalogram (EEG) to provide cognitive indicators for human workload and …
BrainPrint: EEG biometric identification based on analyzing brain connectivity graphs
Research on brain biometrics using electroencephalographic (EEG) signals has received
increasing attentions in recent years. In particular, it has been recognized that the brain …
increasing attentions in recent years. In particular, it has been recognized that the brain …
Biometric identification system using EEG signals
AB Tatar - Neural Computing and Applications, 2023 - Springer
This study focuses on using EEG signal-based behavioral biometric data to classify and
identify persons. A person identification system based on a nonlinear model with excellent …
identify persons. A person identification system based on a nonlinear model with excellent …
[HTML][HTML] Enhancing security in brain–computer interface applications with deep learning: Electroencephalogram-based user identification
Electroencephalogram (EEG) signals have gained widespread use in medical applications,
and the utilization of EEG signals as a biometric feature for user identification systems in …
and the utilization of EEG signals as a biometric feature for user identification systems in …
Cancellable template design for privacy-preserving EEG biometric authentication systems
As a promising candidate to complement traditional biometric modalities, brain biometrics
using electroencephalography (EEG) data has received a widespread attention in recent …
using electroencephalography (EEG) data has received a widespread attention in recent …
Towards online applications of EEG biometrics using visual evoked potentials
Electroencephalogram (EEG)-based biometrics have attracted increasing attention in recent
years. A few studies have used visual evoked potentials (VEPs) in EEG biometrics due to …
years. A few studies have used visual evoked potentials (VEPs) in EEG biometrics due to …
Unsupervised domain adaptation via spatial pattern alignment for VEP-based identity recognition
Electroencephalography (EEG) biometrics has garnered significant attention in recent years
owing to its nonintrusive nature, real-time detection capabilities, concealment, and high …
owing to its nonintrusive nature, real-time detection capabilities, concealment, and high …