Human Gender Classification using Machine Learning
Vaishnavi Y. Mali · International Journal of Engineering Research and · 2019
Human Gender classification is one of the most interested and critical area of research.Research contains interactions between computers and human which includes vast information concerning difference in characteristics of males and females.In several kind of pattern recognition, machine learning gives a relation between gender and face.This paper proposes comparison between different techniques used for gender classification.Face is a unique biometric feature of the individual.Facial images with different combinations including frontal, aligned, smiling, non-smiling as well as expression images make the system complicated.Various face recognition methods such as Convolutional neural networks, Delaunay triangulations, geometry based methods like SVM (Support vector machine), LDA (Linear discriminant analysis).For human gender classification, SVM provides better accuracy as compared with existing methods.