Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …
detect driver inattention is essential in building a safe yet intelligent transportation system …
A survey on vision-based driver distraction analysis
Motor vehicle crashes are great threats to our life, which may result in numerous fatalities, as
well as tremendous economic and societal costs. Driver inattention, either distraction or …
well as tremendous economic and societal costs. Driver inattention, either distraction or …
[HTML][HTML] Automatic driver distraction detection using deep convolutional neural networks
Recently, the number of road accidents has been increased worldwide due to the distraction
of the drivers. This rapid road crush often leads to injuries, loss of properties, even deaths of …
of the drivers. This rapid road crush often leads to injuries, loss of properties, even deaths of …
HCF: A hybrid CNN framework for behavior detection of distracted drivers
C Huang, X Wang, J Cao, S Wang, Y Zhang - IEEE access, 2020 - ieeexplore.ieee.org
Distracted driving causes a large number of traffic accident fatalities and is becoming an
increasingly important issue in recent research on traffic safety. Gesture patterns are less …
increasingly important issue in recent research on traffic safety. Gesture patterns are less …
An efficient deep learning framework for distracted driver detection
F Sajid, AR Javed, A Basharat, N Kryvinska… - IEEE …, 2021 - ieeexplore.ieee.org
The number of road accidents has constantly been increasing recently around the world. As
per the national highway traffic safety administration's investigation, 45% of vehicle crashes …
per the national highway traffic safety administration's investigation, 45% of vehicle crashes …
Toward extremely lightweight distracted driver recognition with distillation-based neural architecture search and knowledge transfer
The number of traffic accidents has been continuously increasing in recent years worldwide.
Many accidents are caused by distracted drivers, who take their attention away from driving …
Many accidents are caused by distracted drivers, who take their attention away from driving …
A hybrid deep learning approach for driver distraction detection
The World Health Organisation reports distracted driving actions as the main cause of road
traffic accidents. Current studies to detect distraction postures focus on analysing spatial …
traffic accidents. Current studies to detect distraction postures focus on analysing spatial …
Distracted driver detection based on a CNN with decreasing filter size
B Qin, J Qian, Y Xin, B Liu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
In recent years, the number of traffic accident deaths due to distracted driving has been
increasing dramatically. Fortunately, distracted driving can be detected by the rapidly …
increasing dramatically. Fortunately, distracted driving can be detected by the rapidly …
CAT-CapsNet: A convolutional and attention based capsule network to detect the driver's distraction
Worldwide inflation in the count of road accidents has raised an alarming scenario wherein
driver distraction is identified as one of the main causes. According to the National Highway …
driver distraction is identified as one of the main causes. According to the National Highway …
Machine learning and end-to-end deep learning for monitoring driver distractions from physiological and visual signals
It is only a matter of time until autonomous vehicles become ubiquitous; however, human
driving supervision will remain a necessity for decades. To assess the driver's ability to take …
driving supervision will remain a necessity for decades. To assess the driver's ability to take …