Exploring gender prediction from digital handwriting

ERBİLEK M., Fairhurst M., Li C.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.789-792, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2016.7495858
  • Basıldığı Şehir: Zonguldak
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.789-792
  • Orta Doğu Teknik Üniversitesi Kuzey Kıbrıs Kampüsü Adresli: Hayır

Özet

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.