Gender prediction

Earlier methods of gender calculation used neural networks. Image intensities and the three-dimensional structure of the face were used to predict gender. SVM classifiers were used for image intensities. 

As a general procedure on all upcoming iOS applications, we will look into code signing and provisioning profiles in this chapter. One of the popular benchmarks for this is the FERET benchmark, which uses intensity, shape, and feature to produce near-perfect performance solutions. The dataset that is used in this application uses a complex set of images that are taken from different angles and are exposed to different amounts of light. Another popular benchmark, called Labeled Faces in the Wild (LFW), uses Local Binary Pattern (LBP) with an AdaBoost classifier.