Using bidirectional long short term memory with attention layer to estimate driver behavior

SM Kouchak, A Gaffar - 2019 18th IEEE International …, 2019 - ieeexplore.ieee.org
Driver distraction is one of the primary causes of fatal car accidents in US Analyzing driver
behavior using different types of data including driving data, driver status or a combination of …

Detecting driver behavior using stacked long short term memory network with attention layer

SM Kouchak, A Gaffar - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Driver distraction is one of the primary reasons for fatal car accidents. Modern cars with
advanced infotainment systems often take some cognitive attention away from the road …

Estimating the driver status using long short term memory

S Monjezi Kouchak, A Gaffar - … and Knowledge Extraction: Third IFIP TC 5 …, 2019 - Springer
Driver distraction is one of the leading causes of fatal car accidents. Driver distraction is any
task that diverts the driver attention from the primary task of driving and increases the driver's …

[HTML][HTML] EFFNet-CA: an efficient driver distraction detection based on multiscale features extractions and channel attention mechanism

T Khan, G Choi, S Lee - Sensors, 2023 - mdpi.com
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 …

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 …

[HTML][HTML] 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 …

AB-DLM: an improved deep learning model based on attention mechanism and BiFPN for driver distraction behavior detection

T Li, Y Zhang, Q Li, T Zhang - IEEE Access, 2022 - ieeexplore.ieee.org
Driver distraction behavior causes a large number of traffic accidents every year, resulting in
economic losses and injuries. Currently, the driver still plays an important role in the driving …

Benchmarking deep learning models for driver distraction detection

J Mafeni Mase, P Chapman, GP Figueredo… - … , Optimization, and Data …, 2020 - Springer
Abstract The World Health Organisation reports distracted driving as one of the main causes
of road traffic accidents. Current studies to detect distraction postures focus on analysing …

Real time detection of driver distraction using CNN

B Janet, US Reddy - 2020 Third International Conference on …, 2020 - ieeexplore.ieee.org
Distracted driving is the main cause for large number of motor vehicle accidents across the
globe. Detecting a distracted driver is considered as the significant research area for …

A hybrid deep learning approach for driver distraction detection

JM Mase, P Chapman, GP Figueredo… - … on information and …, 2020 - ieeexplore.ieee.org
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 …