A Survey on Trustworthy Edge Intelligence: From Security and Reliability to Transparency and Sustainability
Edge Intelligence (EI) integrates Edge Computing (EC) and Artificial Intelligence (AI) to push
the capabilities of AI to the network edge for real-time, efficient and secure intelligent …
the capabilities of AI to the network edge for real-time, efficient and secure intelligent …
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space
Objective. This review paper provides an integrated perspective of Explainable Artificial
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …
[HTML][HTML] A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition
Electroencephalogram (EEG) has become increasingly popular in driver fatigue monitoring
systems. Several decomposition methods have been attempted to analyze the EEG signals …
systems. Several decomposition methods have been attempted to analyze the EEG signals …
Sample-based data augmentation based on electroencephalogram intrinsic characteristics
Deep learning for electroencephalogram-based classification is confronted with data
scarcity, due to the time-consuming and expensive data collection procedure. Data …
scarcity, due to the time-consuming and expensive data collection procedure. Data …
CSF-GTNet: A novel multi-dimensional feature fusion network based on Convnext-GeLU-BiLSTM for EEG-signals-enabled fatigue driving detection
D Gao, P Li, M Wang, Y Liang, S Liu… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Electroencephalography (EEG) signal has been recognized as an effective fatigue detection
method, which can intuitively reflect the drivers' mental state. However, the research on multi …
method, which can intuitively reflect the drivers' mental state. However, the research on multi …
An EEG-based cross-subject interpretable CNN for game player expertise level classification
L Lin, P Li, Q Wang, B Bai, R Cui, Z Yu, D Gao… - Expert Systems with …, 2024 - Elsevier
Electroencephalogram (EEG) signals have been demonstrated to be an effective method for
game player expertise level classification, as it can reflect the activity state of the player's …
game player expertise level classification, as it can reflect the activity state of the player's …
A Robust driver emotion recognition method based on high-purity feature separation
Since emotions generally affect driver's behavior, judgment, and reaction time, accurately
identifying driver's emotions is of great significance to improve the safety and comfort of …
identifying driver's emotions is of great significance to improve the safety and comfort of …
[HTML][HTML] An enhanced ensemble deep random vector functional link network for driver fatigue recognition
This work investigated the use of an ensemble deep random vector functional link (edRVFL)
network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low …
network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low …
Interpretable and robust ai in eeg systems: A survey
The close coupling of artificial intelligence (AI) and electroencephalography (EEG) has
substantially advanced human-computer interaction (HCI) technologies in the AI era …
substantially advanced human-computer interaction (HCI) technologies in the AI era …
An auto-weighting incremental random vector functional link network for EEG-based driving fatigue detection
Recently, electroencephalogram (EEG) has been receiving increasing attention in driving
fatigue attention because it is generated by the neural activities of central nervous system …
fatigue attention because it is generated by the neural activities of central nervous system …