Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks

@article{Oquab2014LearningAT,
  title={Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks},
  author={Maxime Oquab and L{\'e}on Bottou and Ivan Laptev and Josef Sivic},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2014},
  pages={1717-1724}
}
Convolutional neural networks (CNN) have recently shown outstanding image classification performance in the large- scale visual recognition challenge (ILSVRC2012). The success of CNNs is attributed to their ability to learn rich mid-level image representations as opposed to hand-designed low-level features used in other image classification methods. Learning CNNs, however, amounts to estimating millions of parameters and requires a very large number of annotated image samples. This property… CONTINUE READING
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