Corpus ID: 3867935

Low Rank Variation Dictionary and Inverse Projection Group Sparse Representation Model for Breast Tumor Classification

@article{Yang2018LowRV,
  title={Low Rank Variation Dictionary and Inverse Projection Group Sparse Representation Model for Breast Tumor Classification},
  author={Xiaohui Yang and Xiaoying Jiang and Wenming Wu and Juan Zhang and Dan Long and Funa Zhou and Yiming Xu},
  journal={ArXiv},
  year={2018},
  volume={abs/1803.04793}
}
  • Xiaohui Yang, Xiaoying Jiang, +4 authors Yiming Xu
  • Published in ArXiv 2018
  • Computer Science
  • Sparse representation classification achieves good results by addressing recognition problem with sufficient training samples per subject. However, SRC performs not very well for small sample data. In this paper, an inverse-projection group sparse representation model is presented for breast tumor classification, which is based on constructing low-rank variation dictionary. The proposed low-rank variation dictionary tackles tumor recognition problem from the viewpoint of detecting and using… CONTINUE READING

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    Publications referenced by this paper.
    SHOWING 1-10 OF 24 REFERENCES

    Extended SRC: Undersampled Face Recognition via Intraclass Variant Dictionary

    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    Robust Face Recognition via Sparse Representation

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Robust principal component analysis?

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Multiplier and gradient methods

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    RPCA-Based Tumor Classification Using Gene Expression Data

    VIEW 1 EXCERPT

    Group sparse optimization by alternating direction method