Scheduled System Maintenance:
On May 6th, system maintenance will take place from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). During this time, there may be intermittent impact on performance. We apologize for the inconvenience.
By Topic

Sensory perception, learning and integration in neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)
Ishii, N. ; Dept. of Intelligence & Comput. Sci., Nagoya Inst. of Technol., Japan ; Sugiura, S. ; Nakamura, M. ; Yamauchi, K.

In biological visual neural networks, one of the prominent features is nonlinear functions, which play important roles in the visual system. However, the order of the nonlinearity of the visual system is one of the unsolved problems in its processing. The non-Fourier motion is visually perceived motion that cannot be explained simply by the autocorrelation (Fourier motion) of the stimulus. This non-Fourier motion is said to perceive it by the pre-processing of the nonlinearity transformation in the visual system. First, we analyze the structure and the function of the nonlinear asymmetric networks in the visual system. Second, sensory integration is realized by the sensor neural networks, which consist of the forward, backward networks and the integration neuron

Published in:

Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on

Date of Conference: