• DocumentCode
    3333713
  • Title

    Analysis of feature concatenation operation on vector spaces

  • Author

    Özay, Mete ; Vural, Fatos T Yarman

  • Author_Institution
    Bilgisayar Muhendisligi Bolumu, ODTU, Ankara, Turkey
  • fYear
    2010
  • fDate
    22-24 April 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this study, the theoretical and experimental analysis of feature space concatenation operation is introduced. This operation is widely used for data fusion and ensemble learning. Following the analysis, a new performance measure which is called Vectorization Measure (VM) is introduced. VM enables the estimation of the separability capacity of the fusion space by analyzing the sample margin distributions on the feature vector subpsaces.
  • Keywords
    sensor fusion; vectors; data fusion; ensemble learning; feature space concatenation; vector spaces; vectorization measure; Art; Artificial neural networks; Biometrics; Face; Image classification; Kernel; Machine learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th
  • Conference_Location
    Diyarbakir
  • Print_ISBN
    978-1-4244-9672-3
  • Type

    conf

  • DOI
    10.1109/SIU.2010.5651471
  • Filename
    5651471