[HTML][HTML] Representation learning and pattern recognition in cognitive biometrics: a survey

M Wang, X Yin, Y Zhu, J Hu - Sensors, 2022 - mdpi.com
Cognitive biometrics is an emerging branch of biometric technology. Recent research has
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 …

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 …

Convolutional neural networks using dynamic functional connectivity for EEG-based person identification in diverse human states

M Wang, H El-Fiqi, J Hu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
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 …

BrainPrint: EEG biometric identification based on analyzing brain connectivity graphs

M Wang, J Hu, HA Abbass - Pattern Recognition, 2020 - Elsevier
Research on brain biometrics using electroencephalographic (EEG) signals has received
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 …

[HTML][HTML] Enhancing security in brain–computer interface applications with deep learning: Electroencephalogram-based user identification

A Seyfizadeh, RL Peach, P Tovote, IU Isaias… - Expert Systems with …, 2024 - Elsevier
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 …

Cancellable template design for privacy-preserving EEG biometric authentication systems

M Wang, S Wang, J Hu - IEEE Transactions on Information …, 2022 - ieeexplore.ieee.org
As a promising candidate to complement traditional biometric modalities, brain biometrics
using electroencephalography (EEG) data has received a widespread attention in recent …

Towards online applications of EEG biometrics using visual evoked potentials

H Zhao, Y Chen, W Pei, H Chen, Y Wang - Expert Systems with …, 2021 - Elsevier
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 …

Unsupervised domain adaptation via spatial pattern alignment for VEP-based identity recognition

H Zhao, Y Wang, X Gao - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Electroencephalography (EEG) biometrics has garnered significant attention in recent years
owing to its nonintrusive nature, real-time detection capabilities, concealment, and high …