[HTML][HTML] Aviation and neurophysiology: A systematic review
This paper systematically reviews 20 years of publications (N= 54) on aviation and
neurophysiology. The main goal is to provide an account of neurophysiological changes …
neurophysiology. The main goal is to provide an account of neurophysiological changes …
A review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning
Driver fatigue is an essential reason for traffic accidents, which poses a severe threat to
people's lives and property. In this review, we summarize the latest research findings and …
people's lives and property. In this review, we summarize the latest research findings and …
Non-intrusive surrogate modeling for parametrized time-dependent partial differential equations using convolutional autoencoders
This paper presents a novel non-intrusive surrogate modeling scheme based on deep
learning for predictive modeling of complex systems, described by parametrized time …
learning for predictive modeling of complex systems, described by parametrized time …
Self-paced dynamic infinite mixture model for fatigue evaluation of pilots' brains
Current brain cognitive models are insufficient in handling outliers and dynamics of
electroencephalogram (EEG) signals. This article presents a novel self-paced dynamic …
electroencephalogram (EEG) signals. This article presents a novel self-paced dynamic …
Deep learning in EEG: Advance of the last ten-year critical period
Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …
in speech recognition and computer vision. Relatively less work has been done for …
Continuous EEG decoding of pilots' mental states using multiple feature block-based convolutional neural network
Non-invasive brain-computer interface (BCI) has been developed for recognizing and
classifying human mental states with high performances. Specifically, classifying pilots' …
classifying human mental states with high performances. Specifically, classifying pilots' …
[HTML][HTML] Recognition of the mental workloads of pilots in the cockpit using EEG signals
The commercial flightdeck is a naturally multi-tasking work environment, one in which
interruptions are frequent come in various forms, contributing in many cases to aviation …
interruptions are frequent come in various forms, contributing in many cases to aviation …
[HTML][HTML] Classification of drowsiness levels based on a deep spatio-temporal convolutional bidirectional LSTM network using electroencephalography signals
Non-invasive brain-computer interfaces (BCI) have been developed for recognizing human
mental states with high accuracy and for decoding various types of mental conditions. In …
mental states with high accuracy and for decoding various types of mental conditions. In …
Classification of pilots' mental states using a multimodal deep learning network
An automation system for detecting the pilot's diversified mental states is an extremely
important and essential technology, as it could prevent catastrophic accidents caused by the …
important and essential technology, as it could prevent catastrophic accidents caused by the …
Brain-computer interface using brain power map and cognition detection network during flight
This article presents a new aviation brain-computer interface, which includes the
construction of a color brain power map and a cognitive detection network. The developed …
construction of a color brain power map and a cognitive detection network. The developed …