Face recognition with VG-RAM weightless neural networks

Abstract

Virtual Generalizing Random Access Memory Weightless Neural Networks (Vg-ram wnn) are effective machine learning tools that offer simple implementation and fast training and test. We examined the performance of Vg-ram wnn on face recognition using a well known face database-the AR Face Database. We evaluated two Vg-ram wnn architectures configured with different numbers of neurons and synapses per neuron. Our experimental results show that, even when training with a single picture per person, Vg-ram wnn are robust to various facial expressions, occlusions and illumination conditions, showing better performance than many well known face recognition techniques. © Springer-Verlag Berlin Heidelberg 2008.