• DocumentCode
    143116
  • Title

    Learning based data mining using compressed sensing

  • Author

    Gleich, Dusan

  • Author_Institution
    Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor, Slovenia
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    1643
  • Lastpage
    1646
  • Abstract
    This paper presents a categorization of SAR patches using supervised approach within a dictionary learning sparse representation framework. Dictionary learning algorithms represent matrix factorization of data matrix X as the product of Dictionary and sparse coefficients Z. The dictionary learning algorithm was implemented using well known K-SVD algorithm. The trained dictionaries were used for sparse representation and classification. Experimental results showed superior results for Dictionary-Learning Sparse Representation framework for categorization of SAR patches.
  • Keywords
    compressed sensing; geophysical techniques; geophysics computing; remote sensing by radar; synthetic aperture radar; K-SVD algorithm; SAR patches; compressed sensing; data matrix X; dictionary coefficient; dictionary learning algorithm represent matrix factorization; dictionary learning sparse representation framework; dictionary-learning sparse representation framework; learning based data mining; sparse classification; sparse coefficient; supervised approach; Accuracy; Compressed sensing; Databases; Dictionaries; Matching pursuit algorithms; Synthetic aperture radar; Training; Dictionary learning; Synthetic Aperture Radar; categorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6946763
  • Filename
    6946763