Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs

@article{Zhang2020DriverBR,
  title={Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs},
  author={Chaoyun Zhang and R. Li and W. Kim and D. Yoon and Paul Patras},
  journal={IEEE Access},
  year={2020},
  volume={8},
  pages={191138-191151}
}
  • Chaoyun Zhang, R. Li, +2 authors Paul Patras
  • Published 2020
  • Computer Science
  • IEEE Access
    • Understanding driver activity is vital for in-vehicle systems that aim to reduce the incidence of car accidents rooted in cognitive distraction. Automating real-time behavior recognition while ensuring actions classification with high accuracy is however challenging, given the multitude of circumstances surrounding drivers, the unique traits of individuals, and the computational constraints imposed by in-vehicle embedded platforms. Prior work fails to jointly meet these runtime/accuracy… CONTINUE READING
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