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A survey on driver behavior analysis from in-vehicle cameras
Distracted or drowsy driving is unsafe driving behavior responsible for thousands of crashes
every year. Studying driver behavior has challenges associated with observing drivers in …
every year. Studying driver behavior has challenges associated with observing drivers in …
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 …
E2DR: A deep learning ensemble-based driver distraction detection with recommendations model
M Aljasim, R Kashef - Sensors, 2022 - mdpi.com
The increasing number of car accidents is a significant issue in current transportation
systems. According to the World Health Organization (WHO), road accidents are the eighth …
systems. According to the World Health Organization (WHO), road accidents are the eighth …
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 …
[HTML][HTML] Real-time driver distraction recognition: A hybrid genetic deep network based approach
AA Aljohani - Alexandria Engineering Journal, 2023 - Elsevier
Distracting while driving is a serious issue that causes serious direct and indirect harm to the
society. To avoid these problems, detecting dangerous drivers' behaviour is very important …
society. To avoid these problems, detecting dangerous drivers' behaviour is very important …
CBAM VGG16: an efficient driver distraction classification using CBAM embedded VGG16 architecture
Driver monitoring systems (DMS) are crucial in autonomous driving systems (ADS) when
users are concerned about driver/vehicle safety. In DMS, the significant influencing factor of …
users are concerned about driver/vehicle safety. In DMS, the significant influencing factor of …
Evaluating the impact of Heavy Goods Vehicle driver monitoring and coaching to reduce risky behaviour
Determining the impact of driver-monitoring technologies to improve risky driving behaviours
allows stakeholders to understand which aspects of onboard sensors and feedback need …
allows stakeholders to understand which aspects of onboard sensors and feedback need …
A new unsupervised deep learning algorithm for fine-grained detection of driver distraction
Traffic accidents caused by distracted drivers account for a large proportion of traffic
accidents each year, and monitoring the driving state of drivers to avoid traffic accidents …
accidents each year, and monitoring the driving state of drivers to avoid traffic accidents …
In-vehicle sensing for smart cars
Driving safety has been attracting more and more interest due to the unprecedented
proliferation of vehicles and the subsequent increase of traffic accidents. As such the …
proliferation of vehicles and the subsequent increase of traffic accidents. As such the …