研究论文
A smart analysis of driver fatigue and drowsiness detection using convolutional neural networks
Abid Ali Minhas, Sohail Jabbar, Muhammad Farhan, Muhammad Najam-ul-Islam
Al Yamamah University University of Faisalabad COMSATS University Islamabad Bahria University
来源Multimedia Tools and Applications
年份2022
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学术脉络
学科主题
社会科学Sleep and Work-Related Fatigue
IoT and GPS-based Vehicle Safety Systems · Fire Detection and Safety Systems
参考文献 33
Minimizing loss of indoleacetic acid during purification of plant extracts
被引 45Jay D. Mann, Ernest G. Jaworski · Planta · 1970
Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
被引 6,580C. J. Willmott, Kenji Matsuura · Climate Research · 2005
Multilayer feedforward networks with a nonpolynomial activation function can approximate any function
被引 2,163Moshe Leshno, V. Ya. Lin, Allan M. Pinkus · Neural Networks · 1993
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引用本文 38
Machine learning and deep learning techniques for driver fatigue and drowsiness detection: a review
被引 141Samy Abd El‐Nabi, Walid El‐Shafai, El‐Sayed M. El‐Rabaie · Multimedia Tools and Applications · 2023
Real-time driver drowsiness detection using transformer architectures: a novel deep learning approach
被引 95Osama Farouk Hassan, Ahmed Farid Ibrahim, Ahmed Ali Gomaa · Scientific Reports · 2025
Technologies for detecting and monitoring drivers' states: A systematic review
被引 51Maged S. Al-Quraishi, Syed Saad Azhar Ali, Muhammad Al‐Qurishi · Heliyon · 2024
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