Bilinear deep learning for image classification

@inproceedings{Zhong2011BilinearDL,
  title={Bilinear deep learning for image classification},
  author={S. Zhong and Yan Liu and Yang Liu},
  booktitle={MM '11},
  year={2011}
}
  • S. Zhong, Yan Liu, Yang Liu
  • Published in MM '11 2011
  • Computer Science
  • Image classification is a well-known classical problem in multimedia content analysis. This paper proposes a novel deep learning model called bilinear deep belief network (BDBN) for image classification. Unlike previous image classification models, BDBN aims to provide human-like judgment by referencing the architecture of the human visual system and the procedure of intelligent perception. Therefore, the multi-layer structure of the cortex and the propagation of information in the visual areas… CONTINUE READING
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    References

    Publications referenced by this paper.
    SHOWING 1-8 OF 8 REFERENCES
    Discriminative Deep Belief Networks for image classification
    29
    Support Kernel Machines for Object Recognition
    81
    What is the best multi-stage architecture for object recognition?
    1739
    Greedy Layer-Wise Training of Deep Networks
    1616
    Deep learning via semi-supervised embedding
    391
    A training algorithm for optimal margin classifiers
    9167
    Large Scale Transductive SVMs
    432
    Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure
    412