Feature Engineering and Machine Learning for Driver Sleepiness Detection
Falling asleep while operating a moving vehicle is a contributing factor to the statistics of road related accidents. It has been estimated that 20% of all accidents where a vehicle has been involved are due to sleepiness behind the wheel. To prevent accidents and to save lives are of uttermost impo...
Main Authors: | Keelan, Oliver, Mårtensson, Henrik |
---|---|
Format: | Others |
Language: | English |
Published: |
Linköpings universitet, Institutionen för medicinsk teknik
2017
|
Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-142001 |
Similar Items
-
Deep learning to classify driver sleepiness from electrophysiological data
by: Johansson, Ida, et al.
Published: (2019) -
Deep Learning for Driver Sleepiness Classification using Bioelectrical Signals and Karolinska Sleepiness Scale
by: Jonsson, Maja, et al.
Published: (2021) -
Heart rate variability for driver sleepiness assessment
by: Persson, Anna
Published: (2019) -
SLEEPINESS AMONG IRANIAN LORRY DRIVERS
by: K. Sadeghniiat Y. Labbafinejad
Published: (2007-04-01) -
SLEEPINESS AMONG IRANIAN LORRY DRIVERS
by: K. Sadeghniiat Y. Labbafinejad
Published: (2007-06-01)