• DocumentCode
    1863556
  • Title

    Recognizing Adult Image Groups for Web Site Classification

  • Author

    Sun, Hung-Ming

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Kainan Univ., Luchu, Taiwan
  • fYear
    2010
  • fDate
    9-10 Jan. 2010
  • Firstpage
    302
  • Lastpage
    305
  • Abstract
    The recognition accuracy of adult image groups depends on the performance of the adult image recognizer and the final decision rule. Earlier methods of recognizing adult image groups do not take into account the performance tuning of the adult image recognizer but only focus on the decision rule. The proposed method considers the two factors together and resolves optimal parameter settings to achieve the best recognition accuracy for image groups. Experimental results show that the proposed method can attain higher recognition accuracy than the earlier methods.
  • Keywords
    Web sites; image classification; Web site classification; adult image groups; adult image recognizer; decision rule; optimal parameter settings; recognition accuracy; Data mining; Feature extraction; Image databases; Image recognition; Image retrieval; Image segmentation; Neural networks; Skin; Sun; Testing; adult image recognition; image group classification; neural network; web site classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
  • Conference_Location
    Phuket
  • Print_ISBN
    978-1-4244-5397-9
  • Electronic_ISBN
    978-1-4244-5398-6
  • Type

    conf

  • DOI
    10.1109/WKDD.2010.41
  • Filename
    5432616