Results 111 to 120 of about 1,740 (178)

The Effect of Partial Sleep Deprivation and Time-on-Task on Young Drivers' Subjective and Objective Sleepiness. [PDF]

Int J Environ Res Public Health, 2023
Cellini N, Bruno G, Orsini F, Vidotto G, Gastaldi M, Rossi R, Tagliabue M.   +6 more
europepmc   +1 more source

Preliminary development and test of a new automatic drowsiness quantification system using range and intensity images obtained from a dashboard-mounted near-infrared 3D range sensor [PDF]

, 2016
Langohr, Thomas, Massoz, Quentin, Verly, Jacques   +2 more
core  

Improving automatic detection of driver fatigue and distraction using machine learning

Changes and advances in information technology have played an important role in the development of intelligent vehicle systems in recent years. Driver fatigue and distracted driving are important factors in traffic accidents.
Wu, Dongjiang
core  

Attention-based multi-semantic dynamical graph convolutional network for eeg-based fatigue detection. [PDF]

Front Neurosci, 2023
Liu H, Liu Q, Cai M, Chen K, Ma L, Meng W, Zhou Z, Ai Q.   +7 more
europepmc   +1 more source

An EEG-Based technique for operator fatigue determination [PDF]

, 2005
Bongers, D. R.
core  

Forecasting psychomotor vigilance test performance from facial videos. [PDF]

Sleep
Abe T.
europepmc   +1 more source

TMU-Net: A Transformer-Based Multimodal Framework with Uncertainty Quantification for Driver Fatigue Detection. [PDF]

Sensors (Basel)
Zhang Y, Xu X, Du Y, Zhang N.
europepmc   +1 more source

On Fatigue Detection for Air Traffic Controllers Based on Fuzzy Fusion of Multiple Features. [PDF]

Comput Math Methods Med, 2022
Hu Y, Liu Z, Hou A, Wu C, Wei W, Wang Y, Liu M.   +6 more
europepmc   +1 more source

Driving fatigue increases after the Spring transition to Daylight Saving Time in young male drivers: A pilot study.

Transp Res Part F Traffic Psychol Behav, 2023
Orsini F, Giusti G, Zarantonello L, Costa R, Montagnese S, Rossi R.   +5 more
europepmc   +1 more source

A dense multi-pooling convolutional network for driving fatigue detection. [PDF]

Sci Rep
Han Q, Cui S, Min W, Yan C, Liu L, Ning F, Li L.   +6 more
europepmc   +1 more source