Vehicle Type Classification Using Unsupervised Convolutional Neural Network

@article{Dong2014VehicleTC,
  title={Vehicle Type Classification Using Unsupervised Convolutional Neural Network},
  author={Zhen Dong and Mingtao Pei and Yang He and Ting Liu and Yanmei Dong and Yunde Jia},
  journal={2014 22nd International Conference on Pattern Recognition},
  year={2014},
  pages={172-177}
}
In this paper, we propose an appearance-based vehicle type classification method from vehicle frontal view images. Unlike other methods using hand-crafted visual features, our method is able to automatically learn good features for vehicle type classification by using a convolutional neural network. In order to capture rich and discriminative information of vehicles, the network is pre-trained by the sparse filtering which is an unsupervised learning method. Besides, the network is with layer… CONTINUE READING

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Key Quantitative Results

  • The comparison results show that our method achieves 95.7% classification accuracy on daylight images and 88.8% on nightlight images, better than the results of previous methods.

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