A fuzzy recurrent neural network for driver fatigue detection based on steering-wheel angle sensor data
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Abstract
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DOI: 10.1177/1550147719872452
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References listed on IDEAS
- Jaecheul Lee, 2019. "Deep learning–assisted real-time container corner casting recognition," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477188, January.
- Van Quan Nguyen & Tien Nguyen Anh & Hyung-Jeong Yang, 2019. "Real-time event detection using recurrent neural network in social sensors," International Journal of Distributed Sensor Networks, , vol. 15(6), pages 15501477198, June.
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Cited by:
- Zhang, Yu & He, Yingying & Zhang, Likai, 2023. "Recognition method of abnormal driving behavior using the bidirectional gated recurrent unit and convolutional neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
- Ping-Huan Kuo & Ssu-Ting Lin & Jun Hu, 2020. "DNAE-GAN: Noise-free acoustic signal generator by integrating autoencoder and generative adversarial network," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
- Kun Liu & Guoqi Feng & Xingyu Jiang & Wenpeng Zhao & Zhiqiang Tian & Rizheng Zhao & Kaihang Bi, 2023. "A Feature Fusion Method for Driving Fatigue of Shield Machine Drivers Based on Multiple Physiological Signals and Auto-Encoder," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
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Keywords
Fatigue driving features; fuzzy recurrent neural network; steering wheel angle; robust learning;All these keywords.
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