Gender classification from face images using support vector machine
Phyu Phyu Thant.
Date of Issue2004
School of Electrical and Electronic Engineering
Investigated the performance of support vector machine on gender categorization using images. Radial Basic Kernel and two parameters of the RBF kernel were chosen. By using random selection of images for training the classifier in a series of runs, the accuracies were determined.
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems
Nanyang Technological University