Effortless Deep Training for Traffic Sign Detection Using Templates and Arbitrary Natural Images

@article{Tabelini2019EffortlessDT,
  title={Effortless Deep Training for Traffic Sign Detection Using Templates and Arbitrary Natural Images},
  author={Lucas Tabelini and Thiago M. Paix{\~a}o and Rodrigo Berriel and A. Souza and C. Badue and N. Sebe and Thiago Oliveira-Santos},
  journal={2019 International Joint Conference on Neural Networks (IJCNN)},
  year={2019},
  pages={1-7}
}
  • Lucas Tabelini, Thiago M. Paixão, +4 authors Thiago Oliveira-Santos
  • Published 2019
  • Computer Science
  • 2019 International Joint Conference on Neural Networks (IJCNN)
  • Deep learning has been successfully applied to several problems related to autonomous driving. [...] Key Method In this work, we propose a novel database generation method that requires only (i) arbitrary natural images, i.e., requires no real image from the domain of interest, and (ii) templates of the traffic signs, i.e., templates synthetically created to illustrate the appearance of the category of a traffic sign. The effortlessly generated training database is shown to be effective for the training of a…Expand Abstract
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