Deep Learning and Its Applications for Vehicle Networks

2 Deep learning for driver drowsiness classification for a safe vehicle application

Sadegh Arefnezhad and Arno Eichberger

Institute of Automotive Engineering, Graz University of Technology, Graz, Austria

DOI: 10.1201/9781003190691-3

Contents

1. 2.1 Introduction
   • 2.1.1 Importance of drowsiness detection
   • 2.1.2 Application in future automated vehicles
2. 2.2 Driver drowsiness detection methods
   • 2.2.1 Subjective measures
   • 2.2.2 Objective measures
     • 2.2.2.1 Input sources for driver drowsiness detection
   • 2.2.3 Deep learning methods
     • 2.2.3.1 Deep learning methods applied to the biosignals
3. 2.3 Comparison of methods
4. 2.4 Summary and outlook
5. Notes
6. References

2.1 Introduction

2.1.1 Importance of drowsiness detection

Drowsiness is an intermediate condition that ...