Advancing driver fatigue detection in diverse lighting conditions for assisted driving vehicles with enhanced facial recognition technologies

Against the backdrop of increasingly mature intelligent driving assistance systems, effective monitoring of driver alertness during long-distance driving becomes especially crucial. This study introduces a novel method for driver fatigue detection aimed at enhancing the safety and reliability of int...

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Veröffentlicht in:	PloS one 2024-07, Vol.19 (7), p.e0304669
Hauptverfasser:	Lin, Ning, Zuo, Yue
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Adaptability Adult Advanced driver assistance systems Alertness Algorithms Analysis Artificial neural networks Automobile Driving Behavior Biology and Life Sciences Biometry Brightness Computer and Information Sciences Datasets Diagnosis Dimensional analysis Driver fatigue Efficiency Electric lighting Engineering and Technology Environmental conditions Equipment and supplies Face recognition Facial Recognition - physiology Facial recognition technology Fatigue Female Health aspects Humans Identification Lighting Lighting - methods Male Medicine and Health Sciences Network reliability Neural networks Neural Networks, Computer Pattern recognition Physical Sciences Physiological aspects Research and Analysis Methods Roads & highways Social Sciences System effectiveness System reliability Technology application Technology assessment Traffic accidents & safety Traffic safety Vehicles
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