Traffic sign recognition with multi-scale Convolutional Networks

  title={Traffic sign recognition with multi-scale Convolutional Networks},
  author={Pierre Sermanet and Yann LeCun},
  journal={The 2011 International Joint Conference on Neural Networks},
We apply Convolutional Networks (ConvNets) to the task of traffic sign classification as part of the GTSRB competition. ConvNets are biologically-inspired multi-stage architectures that automatically learn hierarchies of invariant features. While many popular vision approaches use hand-crafted features such as HOG or SIFT, ConvNets learn features at every level from data that are tuned to the task at hand. The traditional ConvNet architecture was modified by feeding 1st stage features in… CONTINUE READING
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