Global research on artificial intelligence-enhanced human electroencephalogram analysis
The application of artificial intelligence (AI) technologies in assisting human
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …
EEG-based multi-frequency band functional connectivity analysis and the application of spatio-temporal features in emotion recognition
Y Zhang, G Yan, W Chang, W Huang, Y Yuan - … Signal Processing and …, 2023 - Elsevier
The study of emotional states in brain-computer interface (BCI) has a wide range of
applications in psychiatry, psychology, et al. However, there is few novel feature extraction …
applications in psychiatry, psychology, et al. However, there is few novel feature extraction …
Analysis of factors that influence the performance of biometric systems based on EEG signals
D Carrión-Ojeda, R Fonseca-Delgado… - Expert Systems with …, 2021 - Elsevier
Searching for new biometric traits is currently a necessity because traditional ones such as
fingerprint, voice, or face are highly prone to forgery. For this reason, the study of bioelectric …
fingerprint, voice, or face are highly prone to forgery. For this reason, the study of bioelectric …
Endogenous and exogenous performance sources in Asian Banking: A hybrid stochastic Multi-Criteria Decision-Making approach based on sign decomposition and …
Despite the turmoil in the global financial sector over the years, Asian banking stood still with
many positive characteristics-stable, balanced competition, good governance, and profitable …
many positive characteristics-stable, balanced competition, good governance, and profitable …
A transfer learning-based CNN deep learning model for unfavorable driving state recognition
J Chen, H Wang, E He - Cognitive Computation, 2024 - Springer
The detection of unfavorable driving states (UDS) of drivers based on electroencephalogram
(EEG) measures has received continuous attention from extensive scholars on account of …
(EEG) measures has received continuous attention from extensive scholars on account of …
An ensemble of Xgboost models for detecting disorders of consciousness in brain injuries through EEG connectivity
F Wang, YC Tian, X Zhang, F Hu - Expert Systems with Applications, 2022 - Elsevier
Disorders of consciousness (DoC) happen frequently in brain injuries. Automated DoC
detection is desirable because conventional clinical examinations, typically behavioural …
detection is desirable because conventional clinical examinations, typically behavioural …
Using ResNet transfer deep learning methods in person identification according to physical actions
Today, biometric technologies are one of the areas of information security which are
increasingly used in all areas required by human security. The subjects such as person …
increasingly used in all areas required by human security. The subjects such as person …
EEG-Based Familiar and Unfamiliar Face Classification Using Filter-Bank Differential Entropy Features
The face recognition of familiar and unfamiliar people is an essential part of our daily lives.
However, its neural mechanism and relevant electroencephalography (EEG) features are …
However, its neural mechanism and relevant electroencephalography (EEG) features are …
Review on identity feature extraction methods based on electroencephalogram signals
W Zhong, X An, Y Di, L Zhang, D Ming - … wu yi xue Gong Cheng xue …, 2021 - europepmc.org
生物识别技术在当今信息社会中发挥着重要作用. 脑电信号 (EEG) 作为一种新型的生物特征,
在通用性, 持久性和安全性等方面具有独特优势, 基于脑电信号个体差异性的身份识别研究目前 …
在通用性, 持久性和安全性等方面具有独特优势, 基于脑电信号个体差异性的身份识别研究目前 …
A new approach for human recognition through wearable sensor signals
Recently, subjects such as human recognition (HR), age estimation and gender recognition
have been among the most investigated human–computer interaction topics, in both the …
have been among the most investigated human–computer interaction topics, in both the …