Driver Distraction Detection Using Semi-Supervised Machine Learning

Real-time driver distraction detection is the core to many distraction countermeasures and fundamental for constructing a driver-centered driver assistance system. While data-driven methods demonstrate promising detection performance, a particular challenge is how to reduce the considerable cost for...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2016-04, Vol.17 (4), p.1108-1120
Hauptverfasser:	Liu, Tianchi, Yang, Yan, Huang, Guang-Bin, Yeo, Yong Kiang, Lin, Zhiping
Format:	Artikel
Sprache:	eng
Schlagworte:	Advanced driver assistance system Classification Cost engineering driver distraction Driving conditions eye movement Eyes Feature extraction Intelligent transportation systems Labeling Learning machine learning Neural networks Position measurement Real-time systems semi-supervised learning Semisupervised learning Support vector machines Telematics Training Training data Vehicles
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!