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 …

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 …

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 …

Distracted driving is one of the main causes of deaths and injuries in the world. Monitoring
driver behaviors through Driver Action Recognition (DAR) contributes significantly to …

Automatic recognition and prediction of in-vehicle human activities has a significant impact
on the next generation of driver assistance and intelligent autonomous vehicles. In this …

Real-time running deep convolutional neural networks on embedded electronics is one
recent focus for distracted driving detection. In this work, we proposed, which is a unique …

Driver behavior recognition has become one of the most important tasks for intelligent
vehicles. This task, however, is very challenging since the background contents in real-world …

Traditional methods for behavior detection of distracted drivers are not capable of capturing
driver behavior features related to complex temporal features. With the goal to improve …

Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence
of car accidents rooted in cognitive distraction. Automating real-time behavior recognition …

Distracted driving is one of the top three reasons for traffic fatalities. Every year, thousands of
people are injured or killed in motor vehicle crashes resulting from distracted driving and …