1 February 1991 Multitask neural network for vision machine systems
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Proceedings Volume 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods; (1991) https://doi.org/10.1117/12.25199
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Abstract
A multi-task dynamic neural network that can be programmed for storing processing and encoding spatio-temporal visual information is presented in this paper. This dynamic neural network called the PNnetwork is comprised of numerous densely interconnected neural subpopulations which reside in one of the two coupled sublayers P or N. The subpopulations in the P-sublayer transmit an excitatory or a positive influence onto all interconnected units whereas the subpopulations in the N-sublayer transmit an inhibitory or negative influence. The dynamical activity generated by each subpopulation is given by a nonlinear first-order system. By varying the coupling strength between these different subpopulations it is possible to generate three distinct modes of dynamical behavior useful for performing vision related tasks. It is postulated that the PN-network can function as a basic programmable processor for novel vision machine systems. 1. 0
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Madan M. Gupta, Madan M. Gupta, George K. Knopf, George K. Knopf, } "Multitask neural network for vision machine systems", Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); doi: 10.1117/12.25199; https://doi.org/10.1117/12.25199
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