• DocumentCode
    3490326
  • Title

    ICDAR 2013 Competition on Gender Prediction from Handwriting

  • Author

    Hassaine, Abdulaali ; Al Maadeed, Somaya ; Aljaam, Jihad ; Jaoua, Ali

  • Author_Institution
    Comput. Sci. & Eng. Dept., Qatar Univ., Doha, Qatar
  • fYear
    2013
  • fDate
    25-28 Aug. 2013
  • Firstpage
    1417
  • Lastpage
    1421
  • Abstract
    The prediction of gender from handwriting is a very interesting research field. However, no standard benchmark is available for researchers in this field. The aim of this competition is to gather researchers and compare recent advances in gender prediction from handwriting. This competition has been hosted on Kaggle, it has attracted 194 teams from both academia and industry. This paper gives details on this competition, including the dataset used, the evaluation procedure and description of participating methods and their performances.
  • Keywords
    gender issues; handwriting recognition; ICDAR2013 competition; Kaggle; evaluation procedure; gender prediction; handwriting recognition; participating method description; Boosting; Educational institutions; Feature extraction; Handwriting recognition; Logistics; Principal component analysis; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2013.286
  • Filename
    6628847