Győző Nemes

Gender recognition from mobile biometric data

2016

This paper investigates gender recognition from keystroke dynamics data and from touchscreen swipes. Classification measurements were performed using 10-fold cross-validation and leave-one-user-out cross-validation (LOUOCV). We show that when the target is unseen user data classification, …