Resource-Constrained Machine Learning for ADAS: A Systematic Review

@article{BorregoCarazo2020ResourceConstrainedML,
  title={Resource-Constrained Machine Learning for ADAS: A Systematic Review},
  author={Juan Borrego-Carazo and David Castells-Rufas and Ernesto Biempica and Jordi Carrabina},
  journal={IEEE Access},
  year={2020},
  volume={8},
  pages={40573-40598}
}
  • Juan Borrego-Carazo, David Castells-Rufas, +1 author Jordi Carrabina
  • Published in IEEE Access 2020
  • Computer Science
  • The advent of machine learning (ML) methods for the industry has opened new possibilities in the automotive domain, especially for Advanced Driver Assistance Systems (ADAS). These methods mainly focus on specific problems ranging from traffic sign and light recognition to pedestrian detection. In most cases, the computational resources and power budget found in ADAS systems are constrained while most machine learning methods are computationally intensive. The usual solution consists in adapting… CONTINUE READING

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