Traffic sign recognition with convolutional neural network based on max pooling positions

@article{Qian2016TrafficSR,
  title={Traffic sign recognition with convolutional neural network based on max pooling positions},
  author={Rongqiang Qian and Yong Yue and Frans Coenen and Bailing Zhang},
  journal={2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)},
  year={2016},
  pages={578-582}
}
Recognition of traffic signs is vary important in many applications such as in self-driving car/driverless car, traffic mapping and traffic surveillance. Recently, deep learning models demonstrated prominent representation capacity, and achieved outstanding performance in traffic sign recognition. In this paper, we propose a traffic sign recognition system by applying convolutional neural network (CNN). In comparison with previous methods which usually use CNN as feature extractor and multi… CONTINUE READING
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