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Wild size variable hierarchical network model of retina ganglion cell sensing and its algorithm

A retinal ganglion and network model technology, applied in the field of retinal ganglion cell receptive field scale variable hierarchical network model and its algorithm field, can solve problems such as the decrease of visual cone density, and achieve the effect of simplifying complexity

Inactive Publication Date: 2005-01-12
FUDAN UNIV
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Problems solved by technology

In the area radially arranged from the center of the retina to the periphery, the distribution of cones and rods is mixed, but the density of cones decreases rapidly[5]

Method used

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  • Wild size variable hierarchical network model of retina ganglion cell sensing and its algorithm
  • Wild size variable hierarchical network model of retina ganglion cell sensing and its algorithm
  • Wild size variable hierarchical network model of retina ganglion cell sensing and its algorithm

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Experimental program
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Embodiment Construction

[0042] 1. Realization of variable-scale receptive field

[0043] In the biological retina, the distribution of the size of the receptive field of ganglion cells on the retina increases rapidly from the central fovea to the periphery, and at the same time, the visual acuity decreases rapidly accordingly. We know that the greater the minimum distance between two stimuli that can be distinguished, the smaller the visual acuity. If the ability to distinguish two stimuli is understood as having two different ganglion cells excited, then the visual acuity is related to the diameter of the receptive field. If the distance between the two stimuli is greater than the diameter of the receptive field of the ganglion cells at the corresponding location, it can be inferred that there will be two different ganglion cells that are respectively excited. Since the visual acuity decreases rapidly as the distance from the central fovea increases, when using a function to describe the relationsh...

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Abstract

Basic ideas of the invention are that through simulating information processing flow of early vision of biologic optic nerve system, designing following items solves certain issues. The said items designed in the invention are: layered network structure of simulating layered information processing mode in biologic optic nerve system; computing unit of imitating nerve ganglion, and its variable distribution of sensing field on sensor layer; computing unit for detecting moving orientation in third layer possessing local stage by stage computing mechanism; alertness algorithm for detecting moving event. The invention makes the designed parts release conflict between computing efficiency, precision and computation resources, as well as makes machine vision system pay attention to first important information, meanwhile keep alertness around.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, computer vision, artificial neuron network and cognitive model, and specifically relates to a hierarchical network structure model designed on the basis of the early visual neural mechanism of the biological retina for hierarchical processing of visual image information. It can effectively alleviate the contradiction between computing efficiency, computing accuracy and computing resources, so that the machine vision system can stay alert to the surrounding information while converging the computing power on the primary information. Background technique [0002] Computer vision is a young branch of artificial intelligence. The introduction of Marr's computer vision theory in the early 1980s raised the research level of computer vision to a new level. The visual computing theory holds that such a complex information processing system as the visual system must be studied and understood f...

Claims

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Application Information

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IPC IPC(8): G06N3/02
Inventor 危辉孙慰迟杨显波
Owner FUDAN UNIV
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