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 …
Convolutional neural networks for 5G-enabled intelligent transportation system: A systematic review
Abstract Modern 5G-enabled Intelligent Transportation System (ITS) provides comfort and
safety to the end users by using various models and techniques most of which are based on …
safety to the end users by using various models and techniques most of which are based on …
Driver gaze zone estimation using convolutional neural networks: A general framework and ablative analysis
Driver gaze has been shown to be an excellent surrogate for driver attention in intelligent
vehicles. With the recent surge of highly autonomous vehicles, driver gaze can be useful for …
vehicles. With the recent surge of highly autonomous vehicles, driver gaze can be useful for …
Looking at the driver/rider in autonomous vehicles to predict take-over readiness
N Deo, MM Trivedi - IEEE Transactions on Intelligent Vehicles, 2019 - ieeexplore.ieee.org
Continuous estimation the driver's take-over readiness is critical for safe and timely transfer
of control during the failure modes of autonomous vehicles. In this article, we propose a data …
of control during the failure modes of autonomous vehicles. In this article, we propose a data …
On generalizing driver gaze zone estimation using convolutional neural networks
The knowledge of driver distraction will be important for self driving cars in the near future to
determine the handoff time to the driver. Driver's gaze direction has been previously shown …
determine the handoff time to the driver. Driver's gaze direction has been previously shown …
3D convolutional neural network for object recognition: a review
Recognition of an object from an image or image sequences is an important task in
computer vision. It is an important low-level image processing operation and plays a crucial …
computer vision. It is an important low-level image processing operation and plays a crucial …
Computer vision‐based recognition of driver distraction: A review
Vehicle crash rates caused by distracted driving have been rising in recent years. Hence,
safety while driving on roads is today a crucial concern across the world. Some of the …
safety while driving on roads is today a crucial concern across the world. Some of the …
Driver behavior recognition via interwoven deep convolutional neural nets with multi-stream inputs
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 …
of car accidents rooted in cognitive distraction. Automating real-time behavior recognition …
Deep learning approach based on residual neural network and SVM classifier for driver's distraction detection
In the last decade, distraction detection of a driver gained a lot of significance due to
increases in the number of accidents. Many solutions, such as feature based, statistical …
increases in the number of accidents. Many solutions, such as feature based, statistical …
Driver drowsiness estimation based on factorized bilinear feature fusion and a long-short-term recurrent convolutional network
S Chen, Z Wang, W Chen - Information, 2020 - mdpi.com
The effective detection of driver drowsiness is an important measure to prevent traffic
accidents. Most existing drowsiness detection methods only use a single facial feature to …
accidents. Most existing drowsiness detection methods only use a single facial feature to …