• DocumentCode
    2227162
  • Title

    An Algorithm Based on Imbalance Samples for Vehicle Recognition

  • Author

    Wen, Xuezhi ; Zhao, Yingnan

  • Author_Institution
    Coll. of Comput. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    1120
  • Lastpage
    1123
  • Abstract
    A vehicle recognition algorithm is proposed to solve imbalanced datasets in vehicle recognition based on SVM ensembles. Moreover, an improved Wavelet feature algorithm is also presented. Experimental results show that the presented method has high precision and recall. Furthermore, the system performance can also be improved by increasing learning and has better application.
  • Keywords
    feature extraction; learning (artificial intelligence); object recognition; support vector machines; vehicles; wavelet transforms; SVM ensembles; imbalance samples; imbalanced datasets; vehicle recognition; wavelet feature algorithm; Data mining; Educational institutions; Feature extraction; Information science; Neural networks; Pattern recognition; Software algorithms; Support vector machine classification; Support vector machines; Vehicle detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.229
  • Filename
    5455308