Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation

@inproceedings{Ghifary2016DeepRN,
  title={Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation},
  author={Muhammad Ghifary and W. Kleijn and M. Zhang and D. Balduzzi and W. Li},
  booktitle={ECCV},
  year={2016}
}
  • Muhammad Ghifary, W. Kleijn, +2 authors W. Li
  • Published in ECCV 2016
  • Computer Science
  • In this paper, we propose a novel unsupervised domain adaptation algorithm based on deep learning for visual object recognition. Specifically, we design a new model called Deep Reconstruction-Classification Network (DRCN), which jointly learns a shared encoding representation for two tasks: (i) supervised classification of labeled source data, and (ii) unsupervised reconstruction of unlabeled target data. In this way, the learnt representation not only preserves discriminability, but also… CONTINUE READING
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