Neural Network Controlled Visual Saccades

J. D. Johnson; T. A. Grogan

doi:10.1117/12.952677

29 March 1989 Neural Network Controlled Visual Saccades

J. D. Johnson, T. A. Grogan

Proceedings Volume 1076, Image Understanding and the Man-Machine Interface II; (1989) https://doi.org/10.1117/12.952677
Event: OE/LASE '89, 1989, Los Angeles, CA, United States

Abstract

The paper to be presented will discuss research on a computer vision system controlled by a neural network capable of learning through classical (Pavlovian) conditioning. Through the use of unconditional stimuli (reward and punishment) the system will develop scan patterns of eye saccades necessary to differentiate and recognize members of an input set. By foveating only those portions of the input image that the system has found to be necessary for recognition the drawback of computational explosion as the size of the input image grows is avoided. The model incorporates many features found in animal vision systems, and is governed by understandable and modifiable behavior patterns similar to those reported by Pavlov in his classic study. These behavioral patterns are a result of a neuronal model, used in the network, explicitly designed to reproduce this behavior.

Citation Download Citation

J. D. Johnson and T. A. Grogan "Neural Network Controlled Visual Saccades", Proc. SPIE 1076, Image Understanding and the Man-Machine Interface II, (29 March 1989); https://doi.org/10.1117/12.952677

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