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 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 …
FuseSeg: Semantic segmentation of urban scenes based on RGB and thermal data fusion
Semantic segmentation of urban scenes is an essential component in various applications
of autonomous driving. It makes great progress with the rise of deep learning technologies …
of autonomous driving. It makes great progress with the rise of deep learning technologies …
Real-time machine learning-based driver drowsiness detection using visual features
Drowsiness-related car accidents continue to have a significant effect on road safety. Many
of these accidents can be eliminated by alerting the drivers once they start feeling drowsy …
of these accidents can be eliminated by alerting the drivers once they start feeling drowsy …
Driver stress state evaluation by means of thermal imaging: A supervised machine learning approach based on ECG signal
Featured Application A procedure for a driver's stress state monitoring was provided by
means of thermal infrared imaging. It was validated on ECG-derived parameters through the …
means of thermal infrared imaging. It was validated on ECG-derived parameters through the …
Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review
There are several factors for vehicle accidents during driving such as drivers' negligence,
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …
drowsiness, and fatigue. These accidents can be avoided, if drivers are warned in time …
Classification of drivers' mental workload levels: Comparison of machine learning methods based on ecg and infrared thermal signals
Mental workload (MW) represents the amount of brain resources required to perform
concurrent tasks. The evaluation of MW is of paramount importance for Advanced Driver …
concurrent tasks. The evaluation of MW is of paramount importance for Advanced Driver …
EDDD: Event-based drowsiness driving detection through facial motion analysis with neuromorphic vision sensor
Drowsiness driving is a principal factor of many fatal traffic accidents. This paper presents
the first event-based drowsiness driving detection (EDDD) system by using the recently …
the first event-based drowsiness driving detection (EDDD) system by using the recently …
A systematic review of physiological signals based driver drowsiness detection systems
Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full
mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused …
mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused …
NeuroIV: Neuromorphic vision meets intelligent vehicle towards safe driving with a new database and baseline evaluations
Neuromorphic vision sensors such as the Dynamic and Active-pixel Vision Sensor (DAVIS)
using silicon retina are inspired by biological vision, they generate streams of asynchronous …
using silicon retina are inspired by biological vision, they generate streams of asynchronous …