Modeling of local neural networks of the visual cortex and applications to image processing

Ilya A. Rybak; Natalia A. Shevtsova; Lubov N. Podladchikova

doi:10.1117/12.45010

1 August 1991 Modeling of local neural networks of the visual cortex and applications to image processing

Ilya A. Rybak, Natalia A. Shevtsova, Lubov N. Podladchikova

Proceedings Volume 1469, Applications of Artificial Neural Networks II; (1991) https://doi.org/10.1117/12.45010
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

A model of an iso-orientation domain in the visual cortex is developed. The iso-orientation domain is represented as a neural network with retinotopically organized afferent inputs and anisotropic lateral inhibition formed by feedback connections via inhibitory interneurons. Temporal dynamics of neuron responses to oriented stimuli is studied. The results of computer simulations are compared with those of neurophysiological experiments. It is shown that the later phase of a neuron response has a more sharp orientation tuning than the initial one. It is suggested that the initial phase of a neuron response encodes intensity parameters of visual stimuli, whereas the later phase encodes its orientation. The design of the neural network preprocessor and the architecture of the system for visual information processing, based on the idea of parallel-sequential processing, are proposed. An example of a test image processing is presented.

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Ilya A. Rybak, Natalia A. Shevtsova, and Lubov N. Podladchikova "Modeling of local neural networks of the visual cortex and applications to image processing", Proc. SPIE 1469, Applications of Artificial Neural Networks II, (1 August 1991); https://doi.org/10.1117/12.45010

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