Face recognition using a hybrid supervised unsupervised neural network

A system for automatic face recognition is presented. It consists of several steps. Automatic detection of the eyes and mouth is followed by a spatial normalization of the images. The classification of the normalized images is carried out by a hybrid (supervised and unsupervised) Neural Network. Two methods for reducing the overfitting - a common problem in high-dimensional classification schemes - are presented, and the superiority of their combination is demonstrated.