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    Robust tensor analysis with l1-norm

    Pang, Y. and Li, Xuelong and Yuan, Y. (2010) Robust tensor analysis with l1-norm. IEEE Transactions on Circuits and Systems for Video Technology 20 (2), pp. 172-178. ISSN 1051-8215.

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    Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach.


    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Sarah Hall
    Date Deposited: 20 Jun 2013 10:36
    Last Modified: 09 Aug 2023 12:33


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