Tim Schäck

11 papers B 1Misc 1Journal 5Unranked 4
YearRankTypeTitle / Venue / Authors
2022 J jnl
Comparative Analysis of Vehicle-Based and Driver-Based Features for Driver Drowsiness Monitoring by Support Vector Machines.
IEEE Trans. Intell. Transp. Syst.
Mohamed Hedi Baccour, Frauke Driewer, Tim Schäck, Enkelejda Kasneci
2020 B conf
Camera-based Driver Drowsiness State Classification Using Logistic Regression Models.
SMC
Mohamed Hedi Baccour, Frauke Driewer, Tim Schäck, Enkelejda Kasneci
2020 — conf
Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithm.
SSCI
Mariella Dreissig, Mohamed Hedi Baccour, Tim Schäck, Enkelejda Kasneci
2020 J jnl
Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithm.
CoRR
Mariella Dreissig, Mohamed Hedi Baccour, Tim Schäck, Enkelejda Kasneci
2018 Misc conf
Hands-on in Signal Processing Education at Technische Universitat Darmstadt.
ICASSP
Tim Schäck, Michael Muma, Abdelhak M. Zoubir
2018 J jnl
Robust Nonlinear Causality Analysis of Nonstationary Multivariate Physiological Time Series.
IEEE Trans. Biomed. Eng.
Tim Schäck, Michael Muma, Mengling Feng, Cuntai Guan, Abdelhak M. Zoubir
2017 — conf
Computationally efficient algorithm for photoplethysmography-based atrial fibrillation detection using smartphones.
EMBC
Tim Schäck, Yosef Safi Harb, Michael Muma, Abdelhak M. Zoubir
2017 — conf
Computationally efficient heart rate estimation during physical exercise using photoplethysmographic signals.
EUSIPCO
Tim Schäck, Michael Muma, Abdelhak M. Zoubir
2017 J jnl
Signal Processing Projects at Technische Universität Darmstadt: How to engage undergraduate students in signal processing practice.
IEEE Signal Process. Mag.
Tim Schäck, Michael Eric Muma, Abdelhak M. Zoubir
2016 J jnl
A procedure to locate the eyelid position in noisy videokeratoscopic images.
EURASIP J. Adv. Signal Process.
Tim Schäck, Michael Muma, Weaam Alkhaldi, Abdelhak M. Zoubir
2015 — conf
A new method for heart rate monitoring during physical exercise using photoplethysmographic signals.
EUSIPCO
Tim Schäck, Christian Sledz, Michael Muma, Abdelhak M. Zoubir