A what-and-where neural network for invariant image processing

Abstract

A feedforward neural network for invariant image preprocessing is proposed that represents the position, orientation and size of an image figure (where it is) in a multiplexed spatial map. This map is used to generate an invariant representation of the figure that is insensitive to position, orientation, and size for purposes of pattern recognition (what it is). A multiscale array of oriented filters, followed by competition between orientations and scales is used to define the Where filter.