Results 201 to 210 of about 2,034 (255)

Artificial Intelligence-Based Depression Detection. [PDF]

Sensors (Basel)
Kiss G, Viktor P.
europepmc   +1 more source

The distraction potential of driving a partially automated vehicle through a construction zone. [PDF]

Sci Rep
Biondi F, Sahoo P, Jajo N.
europepmc   +1 more source

A novel paradigm for identifying eye-tracking metrics associated with cognitive control during driving through MEG neuroimaging. [PDF]

Transp Res Part F Traffic Psychol Behav
Seacrist T, Walshe EA, Cheng S, Brown E, Birnbaum C, Kaufman V, Winston FK, Gaetz WC.   +7 more
europepmc   +1 more source

Smart Surface of Steering Wheel Based on Triboelectric Nanogenerator and Artificial Intelligence in Driving Monitoring System. [PDF]

Nanomaterials (Basel)
Fan F, E S, Kang M, Fan Y, Song Q, Xie Y, Zhou Y, Nie J, Cui X, Zhang Y.   +9 more
europepmc   +1 more source

EFFNet-CA: An Efficient Driver Distraction Detection Based on Multiscale Features Extractions and Channel Attention Mechanism [PDF]

Sensors, 2023
Sokjoon Lee, Gyuho Choi
exaly   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

Multimodal Detection of Drivers Drowsiness and Distraction

Proceedings of the 2021 International Conference on Multimodal Interaction, 2021
Considering the ever-growing presence of automobiles around the world, ensuring the safety of those on and near roadways is of great importance. From the causes of accidents, drowsiness and distractedness are among the most consequential. In this paper, we use a multimodal dataset consisting of 11 recorded channels over 45 subjects to model driver’s ...
Kapotaksha Das, Salem Sharak, Kais Riani, Mohamed Abouelenien, Mihai Burzo, Michalis Papakostas   +5 more
openaire   +1 more source

Driver Distraction Detection and Recognition

Volume 14: Safety Engineering, Risk, and Reliability Analysis, 2020
Abstract Statistics have shown that the main reason for traffic accidents is human error. Modern vehicles are equipped to protect occupants in the event of a crash. The latest advanced vehicles come with driver behavior monitoring systems in recent years, and many have been proven to be effective systems in the prevention of accidents ...
Kiran Kumar Chinta, Fred Barez
openaire   +1 more source

Detecting Driver Distraction Using Smartphones

2015 IEEE 29th International Conference on Advanced Information Networking and Applications, 2015
Cell phone usage while driving is a major distraction. Due to the number of accidents that are related to cell phone use while driving, laws have been introduced making the use of a cell phone while driving illegal in several jurisdictions. In this paper, we address a fundamental problem of distinguishing the driver from passengers using ubiquitous ...
Vamsi Paruchuri, Aravind Kumar
openaire   +1 more source