Driver distraction detection using deep neural network
S Monjezi Kouchak, A Gaffar - … , LOD 2019, Siena, Italy, September 10–13 …, 2019 - Springer
Driver distraction, drunk driving and speed are three main causes of fatal car crashes.
Interacting with intricated infotainment system of modern cars increases the driver's cognitive …
Interacting with intricated infotainment system of modern cars increases the driver's cognitive …
[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 …
Real-time distraction detection from driving data based personal driving model using deep learning
K Nakano, B Chakraborty - International Journal of Intelligent …, 2022 - Springer
Distracted driving is one of the main cause of traffic accidents. Car manufacurers are now
developing various driving support systems to ensure safe driving because it is an important …
developing various driving support systems to ensure safe driving because it is an important …
Real-time driver distraction detection system using convolutional neural networks
K Kapoor, R Pamula, SV Murthy - … of ICETIT 2019: Emerging Trends in …, 2020 - Springer
Road crashes have emerged as one of the top causes of death among the most productive
age group. According to the World Health Organization (WHO), in the last decade 1.3 million …
age group. According to the World Health Organization (WHO), in the last decade 1.3 million …
A deep learning approach to driver distraction detection of using mobile phone
Q Xiong, J Lin, W Yue, S Liu, Y Liu… - 2019 IEEE Vehicle …, 2019 - ieeexplore.ieee.org
Using mobile phone while driving is a big threat to traffic safety. In the rail transit, in order to
prevent the driver from being distracted by the mobile phone, the real-time monitoring of …
prevent the driver from being distracted by the mobile phone, the real-time monitoring of …
Real‐time detection of distracted driving based on deep learning
Driver distraction is a leading factor in car crashes. With a goal to reduce traffic accidents
and improve transportation safety, this study proposes a driver distraction detection system …
and improve transportation safety, this study proposes a driver distraction detection system …
Driver distraction detection using single convolutional neural network
Driver status detection is an essential task because driver distraction, fatigue, and
drowsiness of driver are serious causes of traffic accident in recent. In this paper, we focus …
drowsiness of driver are serious causes of traffic accident in recent. In this paper, we focus …
[HTML][HTML] 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 …
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 …
[HTML][HTML] EFFNet-CA: an efficient driver distraction detection based on multiscale features extractions and channel attention mechanism
Driver distraction is considered a main cause of road accidents, every year, thousands of
people obtain serious injuries, and most of them lose their lives. In addition, a continuous …
people obtain serious injuries, and most of them lose their lives. In addition, a continuous …