DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

  title={DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition},
  author={Jeff Donahue and Yangqing Jia and Oriol Vinyals and Judy Hoffman and Ning Zhang and Eric Tzeng and Trevor Darrell},
We evaluate whether features extracted from the activation of a deep convolutional network trained in a fully supervised fashion on a large, fixed set of object recognition tasks can be repurposed to novel generic tasks. Our generic tasks may differ significantly from the originally trained tasks and there may be insufficient labeled or unlabeled data to conventionally train or adapt a deep architecture to the new tasks. We investigate and visualize the semantic clustering of deep convolutional… CONTINUE READING
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Dlid : Deep learning for domain adaptation by interpolating between domains

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