Corpus ID: 202565721

Human-Machine Collaborative Design for Accelerated Design of Compact Deep Neural Networks for Autonomous Driving

@article{Shafiee2019HumanMachineCD,
  title={Human-Machine Collaborative Design for Accelerated Design of Compact Deep Neural Networks for Autonomous Driving},
  author={M. Shafiee and M. Nentwig and Y. Kassahun and Francis Li and Stanislav Bochkarev and Akif Kamal and David Dolson and Secil Altintas and Arif Virani and A. Wong},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.05587}
}
An effective deep learning development process is critical for widespread industrial adoption, particularly in the automotive sector. A typical industrial deep learning development cycle involves customizing and re-designing an off-the-shelf network architecture to meet the operational requirements of the target application, leading to considerable trial and error work by a machine learning practitioner. This approach greatly impedes development with a long turnaround time and the… Expand
Real-Time Notification System of Moving Obstacles in Vehicle-Camera Images Using SSD and Safe Zones

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