Driver Drowsiness Detection using Deep Neural Networks

Sadegh Arefnezhad; Arno Eichberger; Matthias Frühwirth; Ioana Victoria Koglbauer; Clemens  Kaufmann

Driver Drowsiness Detection using Deep Neural Networks

Sadegh Arefnezhad
, Arno Eichberger
, Matthias Frühwirth
, Ioana Victoria Koglbauer
, Clemens Kaufmann

Research output: Contribution to conference › Poster

Original language	English
Publication status	Published - 2022
Event	35. VDI-Fachtagung Fahrerassistenzsysteme und Automatisiertes Fahren Fahrerassistenzsysteme - Aachen, Novotel Aachen City, Aachen, Germany Duration: 17 May 2022 → 18 May 2022 https://www.vdi-wissensforum.de/weiterbildung-automobil/vdivw-tagung-fahrerassistenzsysteme/

Conference

Conference	35. VDI-Fachtagung Fahrerassistenzsysteme und Automatisiertes Fahren Fahrerassistenzsysteme
Country/Territory	Germany
City	Aachen
Period	17/05/22 → 18/05/22
Internet address	https://www.vdi-wissensforum.de/weiterbildung-automobil/vdivw-tagung-fahrerassistenzsysteme/

Keywords

Deep Learning
Driver drowsiness detection
Vehicle
biosignal processing

Fields of Expertise

Mobility & Production

WACHsens - Evaluation of driver performance in semi-automated driving by physiologic, driver behavior and video based sensors
Eichberger, A. (Project manager on research unit)
1/05/17 → 30/04/19
Project: Research project
DVS: Vehicle Dynamics
Khoshnood Sarabi, N. (Attendee), Eichberger, A. (Coordinator), Bernsteiner, S. (Attendee), Li, H. (Attendee), Peer, M. (Attendee), Kanuric, T. (Attendee), De Cristofaro, F. (Attendee), Samiee, S. (Attendee), Arefnezhad, S. (Attendee), Karoshi, P. (Attendee), Puščul, D. (Attendee), Schöttel, C. E. (Other function), Bui, D. T. (Attendee), Malić, D. (Attendee), Semmer, M. (Attendee), Ager, M. (Attendee), Plöckinger, M. (Attendee), Schabauer, M. (Attendee), Harcevic, A. (Attendee), Mihalj, T. (Attendee), Hirschberg, W. (Attendee), Gu, Z. (Attendee), Koglbauer, I. V. (Attendee), Zhao, Y. (Attendee), Magosi, Z. F. (Contact person), Pandurevic, A. (Attendee), Sternat, A. S. (Other function), Wallner, D. (Attendee), Scherndl, C. (Attendee), Shao, L. (Attendee), Rogic, B. (Attendee), Hackl, A. (Attendee), Wellershaus, C. (Attendee), Orucevic, F. (Attendee), Soboleva, K. (Other function), Kraus, H. (Attendee), Nalic, D. (Attendee), Lex, C. (Contact person), Bodner, J. (Other function) & Wohlfahrter, H. (Attendee)
1/01/11 → 31/12/24
Project: Research area

Deep Learning for Driver Drowsiness Classification for safe vehicle application
Arefnezhad, S. & Eichberger, A., 2023, Deep Learning and Its Applications for Vehicle Networks. Hu , F. & Rasheed, I. (eds.). CRC Press, p. 17-37 21 p.
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
Driver Drowsiness Estimation Using EEG Signals with a Dynamical Encoder-Decoder Modeling Framework
Arefnezhad, S., Hamet, J., Eichberger, A., Frühwirth, M., Ischebeck, A., Koglbauer, I. V., Moser, M. & Yousefi, A., Dec 2022, In: Scientific Reports. 12, 1, 1 p., 2650.
Research output: Contribution to journal › Article › peer-review

Open Access
Driver Monitoring of Automated Vehicles by Classification of Driver Drowsiness using a Deep Convolutional Neural Network Trained by Scalograms of ECG Signals
Arefnezhad, S., Eichberger, A., Frühwirth, M., Kaufmann, C., Moser , M. & Koglbauer, I. V., 10 Jan 2022, In: Energies. 15, 2, 25 p., 480.
Research output: Contribution to journal › Article › peer-review

Open Access

Cite this

@conference{601aaff5478e4412baff4d83f78b22a9,

title = "Driver Drowsiness Detection using Deep Neural Networks",

keywords = "Deep Learning, Driver drowsiness detection, Vehicle, biosignal processing",

author = "Sadegh Arefnezhad and Arno Eichberger and Matthias Fr{\"u}hwirth and Koglbauer, \{Ioana Victoria\} and Clemens Kaufmann",

year = "2022",

language = "English",

note = "35. VDI-Fachtagung Fahrerassistenzsysteme und Automatisiertes Fahren Fahrerassistenzsysteme<br/> ; Conference date: 17-05-2022 Through 18-05-2022",

url = "https://www.vdi-wissensforum.de/weiterbildung-automobil/vdivw-tagung-fahrerassistenzsysteme/",

}

TY - CONF

T1 - Driver Drowsiness Detection using Deep Neural Networks

AU - Arefnezhad, Sadegh

AU - Eichberger, Arno

AU - Frühwirth, Matthias

AU - Koglbauer, Ioana Victoria

AU - Kaufmann, Clemens

PY - 2022

Y1 - 2022

KW - Deep Learning

KW - Driver drowsiness detection

KW - Vehicle

KW - biosignal processing

M3 - Poster

T2 - 35. VDI-Fachtagung Fahrerassistenzsysteme und Automatisiertes Fahren Fahrerassistenzsysteme<br/>

Y2 - 17 May 2022 through 18 May 2022

ER -

Driver Drowsiness Detection using Deep Neural Networks

Conference

Keywords

Fields of Expertise

Projects

WACHsens - Evaluation of driver performance in semi-automated driving by physiologic, driver behavior and video based sensors

DVS: Vehicle Dynamics

Research output

Deep Learning for Driver Drowsiness Classification for safe vehicle application

Driver Drowsiness Estimation Using EEG Signals with a Dynamical Encoder-Decoder Modeling Framework

Driver Monitoring of Automated Vehicles by Classification of Driver Drowsiness using a Deep Convolutional Neural Network Trained by Scalograms of ECG Signals

Cite this