Exploring gender prediction from digital handwriting

ERBİLEK M., Fairhurst M., Li C.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.789-792, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2016.7495858
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.789-792
  • Middle East Technical University Northern Cyprus Campus Affiliated: No

Abstract

This paper introduces an empirical investigation which directly addresses and explores gender prediction capacity from digitised handwriting data from several different perspectives - such as feature type (static/dynamic) and content (fixed/variable) types - in order to provide extensive experimental evidence and analysis to guide the development of a better understanding of the opportunities for and practical consequences of gender prediction from digital handwriting data.