• DocumentCode
    2892130
  • Title

    Feature Extraction and Selection in Ground Penetrating Radar with Experimental Data Set of Inclusions in Concrete Blocks

  • Author

    Queiroz, F.A.A. ; Vieira, D.A.G. ; Travassos, X.L. ; Pantoja, M.F.

  • Author_Institution
    Handcrafted Technol., ENACOM, Belo Horizonte, Brazil
  • Volume
    2
  • fYear
    2012
  • fDate
    12-15 Dec. 2012
  • Firstpage
    48
  • Lastpage
    53
  • Abstract
    Ground Penetrating Radar systems have been successfully used to access concrete structures conditions. Moreover, inclusions in concrete can be discriminated by simple models based on traces obtained by GPR. In this work, concrete blocks with different inclusions were probed in controlled conditions. Some features were extracted from Ascans of this experimental data set. To get efficient models, raw data were submitted to features selection and space reduction methods. Without complex data pre-processing, good accuracy and more explainable models with less computational burden were obtained.
  • Keywords
    concrete; feature extraction; ground penetrating radar; radar imaging; A-scans; GPR; complex data preprocessing; concrete blocks inclusions; concrete structures condition access; experimental data set; feature extraction; feature selection; ground penetrating radar; space reduction methods; Concrete; Delay; Machine learning; Concrete; Ground Penetrating Radar; Iterative Search Margin Based Algorithm; Principal Components Analysis; k-Nearest Neighbor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2012 11th International Conference on
  • Conference_Location
    Boca Raton, FL
  • Print_ISBN
    978-1-4673-4651-1
  • Type

    conf

  • DOI
    10.1109/ICMLA.2012.139
  • Filename
    6406724