Research on Driver Status Recognition System of Intelligent Vehicle Terminal Based on Deep Learning
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Methods
2.1.1. Convolutional Neural Network
2.1.2. 3D Convolutional Neural Network
2.1.3. YOLOv3
2.1.4. Advantages of YOLOv3
2.2. Experiments
2.2.1. Experimental Environment Construction
2.2.2. Data Set Production
3. Results
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Xu, Y.; Peng, W.; Wang, L. Research on Driver Status Recognition System of Intelligent Vehicle Terminal Based on Deep Learning. World Electr. Veh. J. 2021, 12, 137. https://doi.org/10.3390/wevj12030137
Xu Y, Peng W, Wang L. Research on Driver Status Recognition System of Intelligent Vehicle Terminal Based on Deep Learning. World Electric Vehicle Journal. 2021; 12(3):137. https://doi.org/10.3390/wevj12030137
Chicago/Turabian StyleXu, Yiming, Wei Peng, and Li Wang. 2021. "Research on Driver Status Recognition System of Intelligent Vehicle Terminal Based on Deep Learning" World Electric Vehicle Journal 12, no. 3: 137. https://doi.org/10.3390/wevj12030137
APA StyleXu, Y., Peng, W., & Wang, L. (2021). Research on Driver Status Recognition System of Intelligent Vehicle Terminal Based on Deep Learning. World Electric Vehicle Journal, 12(3), 137. https://doi.org/10.3390/wevj12030137