A review of recent developments in driver drowsiness detection systems
Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …
decade have led to improvements in driver monitoring systems. Numerous experimental …
A review of EEG signal features and their application in driver drowsiness detection systems
Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …
is often approached using neurophysiological signals as the basis for building a reliable …
SPWVD-CNN for automated detection of schizophrenia patients using EEG signals
Schizophrenia (SZ) is a psychiatric disorder characterized by cognitive dysfunctions,
hallucinations, and delusions, which may lead to lifetime disability. Detection and diagnosis …
hallucinations, and delusions, which may lead to lifetime disability. Detection and diagnosis …
IoT‐based smart alert system for drowsy driver detection
In current years, drowsy driver detection is the most necessary procedure to prevent any
road accidents, probably worldwide. The aim of this study was to construct a smart alert …
road accidents, probably worldwide. The aim of this study was to construct a smart alert …
Multi-model LSTM-based convolutional neural networks for detection of apple diseases and pests
In this paper, we proposed Multi-model LSTM-based Pre-trained Convolutional Neural
Networks (MLP-CNNs) as an ensemble majority voting classifier for the detection of plant …
Networks (MLP-CNNs) as an ensemble majority voting classifier for the detection of plant …
EEG-based mental workload estimation using deep BLSTM-LSTM network and evolutionary algorithm
The mental workload can be estimated by monitoring different mental states from neural
activity. The spectral power of EEG and Event-Related Potentials (ERPs) are the two …
activity. The spectral power of EEG and Event-Related Potentials (ERPs) are the two …
Intelligent driver drowsiness detection for traffic safety based on multi CNN deep model and facial subsampling
Facts reveal that numerous road accidents worldwide occur due to fatigue, drowsiness, and
distraction while driving. Few works on the automated drowsiness detection problem …
distraction while driving. Few works on the automated drowsiness detection problem …
Adaptive Tunable Q Wavelet Transform-Based Emotion Identification
Emotion is a neuronic transient that drives a person to a certain action. Emotion recognition
from electroencephalogram (EEG) signals plays a vital role in the development of a brain …
from electroencephalogram (EEG) signals plays a vital role in the development of a brain …
Non-invasive driver drowsiness detection system
Drowsiness when in command of a vehicle leads to a decline in cognitive performance that
affects driver behavior, potentially causing accidents. Drowsiness-related road accidents …
affects driver behavior, potentially causing accidents. Drowsiness-related road accidents …
Automatic classification methods for detecting drowsiness using wavelet packet transform extracted time-domain features from single-channel EEG signal
S Chinara - Journal of neuroscience methods, 2021 - Elsevier
Background Detecting human drowsiness during some critical works like vehicle driving,
crane operating, mining blasting, etc. is one of the safeguards to prevent accidents. Among …
crane operating, mining blasting, etc. is one of the safeguards to prevent accidents. Among …