Using CMU PIE Human Face Database to a Convolutional Neural Network- Neocognitron

This work presents the application of Neocognitron to the human face recognition. Using a large-scale human face database (CMU PIE), the optimal thresholds of the Neocognitron to human face recognition are verified. During the first experiment, increasing the activation thresholds of the Neocognitron, their best values to be used in the second experiment, increasing the number of training images per subjects, are obtained. As a result it is verified that a number of 25 training images per subjects is enough to obtain very high recognition rate (98%) to the frontal pose images from the database. 350 validation images, non-overlapping with the training images, were used. 1