Gender Classification from Behavioural Biometric Data using Convolutional Neural Network
Sathish Kumar, Shivanand S. Gornale, Rashmi Siddalingappa · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2023
Biometric modalities are used to identify the gender of an individual based upon their physiometrics or behaviometric data.Gender plays a crucial role in most applications like banking, security, document authorization, forensics, psychology, human-computer interventions, and many more.Gender classification using handwritten signatures is still considered to be a challenging task due to homogenous variations among male and female handwritten signatures.This paper monologues the gender classification from offline signature images using Convolutional Neural Network features.The results obtained are promising and competitive with state-of-art techniques.