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A preprocessor based on a computational model of simple cells in the mammalian primary visual cortex is combined with a self-organising artificial neural network in order to to set up an image classification system. After learning with a sequence of input images, the output units of the system turn out to correspond to classes of input images. Notably, a group of output units which are selective for images of human faces emerges. These units mimic the behaviour of face selective cells that have been found in the inferior temporal cortex of primates.

Use of cortical filters and neural networks in a self-organising image classification system