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On the Feasibility of Real-Time Prediction of Driver's Traf..:
, In:
2022 IEEE International Conference on Vehicular Electronics and Safety (ICVES)
,
Garcia, John
;
Arias-Rojas, Wilson
;
Hernandez, German
- p. 1-5 , 2022
Link:
https://doi.org/10.1109/ICVES56941.2022.9987094
RT T1 <cTitle>2022 IEEE International Conference on Vehicular Electronics and Safety (ICVES)</cTitle>: T1 <Title>On the Feasibility of Real-Time Prediction of Driver's Traffic Accident Risk with Auto ML using Demographics and Brain Concentration Levels Information</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9987094&Exemplar=1&LAN=DE A1 Garcia, John A1 Arias-Rojas, Wilson A1 Hernandez, German YR 2022 K1 Machine learning K1 Predictive models K1 Brain modeling K1 Real-time systems K1 Data models K1 Safety K1 Accidents K1 Concentration K1 brain waves K1 brain waves sensor K1 real time prediction K1 demographics K1 drivers accident risk K1 auto machine learning SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/ICVES56941.2022.9987094 DO https://doi.org/10.1109/ICVES56941.2022.9987094 SF ELIB - SuUB Bremen
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