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Method for simulating attention mobility by using neural network

A neural network and network technology, applied in the field of image processing and neural network, can solve problems that researchers know little about

Active Publication Date: 2010-11-24
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0003] When the human eye processes visual images, it can easily perceive and understand in a short period of time, and realize the transfer from one salient area to the next salient area. The mechanism is still poorly understood

Method used

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  • Method for simulating attention mobility by using neural network
  • Method for simulating attention mobility by using neural network
  • Method for simulating attention mobility by using neural network

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Embodiment Construction

[0052] The specific embodiments of the present invention will be described below with reference to the drawings.

[0053] The system is divided into three parts, the visual image input layer, the neuron vibrator network oscillation layer, and the transfer realization layer. The relationship between the three layers is like figure 1 Note that the structure diagram of the transfer system is shown.

[0054] The system first establishes a one-to-one association between each pixel in a visual image and all neuron vibrators in the neural dynamic network, and then makes this group of neuron vibrators oscillate. Since objects with high brightness stimulate the retina of human eyes more strongly, I input The increase in the frequency leads to an increase in the firing frequency, and the firing process will inhibit other areas.

[0055] Arrange the single neurons described by the FHN model in the form of a matrix and reconstruct the model to form a neural dynamic network. In the newly estab...

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Abstract

The invention discloses a method for simulating attention mobility by using a neural network, which adopts a visual image input layer, neuronal oscillator network oscillation layer and an attention mobility realizing layer, wherein the visual image input layer inputs a gray value of a gray level image into a neurodynamic network; the neuronal oscillator network oscillation layer couples dynamic systems, which are built by all oscillators in the neurodynamic network according to a FitzHugh-Nagumo model, to form the neurodynamic network; and the attention mobility realizing layer realizes the attention mobility between the synchronized different objects by changing parameters, so that the frequency output by nerves of a currently concerned object increases. On the basis of the neurodynamic system, the method forms simple simulation on human-eye attention mobility visual treatment by analyzing and modifying the FitzHugh-Nagumo model and has a great theoretical and practical significance for further research on the visual treatment mechanism of human.

Description

Technical field [0001] The present invention relates to image processing and neural network technology based on neural dynamics, in particular to a neural dynamic network formed by neuron oscillators described by a neural dynamics model, which is used to simulate human attention in simple artificial gray-scale images Method of transfer. Background technique [0002] Visual attention selection and visual attention transfer are important mechanisms to ensure that biological systems complete tasks with limited processing power. Extracting salient features from images or receptive fields and dividing them into different regions is the fundamental task of perception and understanding. This ability is the choice of visual attention in visual understanding. When the salient area is selected, due to the adaptability of the visual system, the attention will shift from the current salient area to the next salient area, which is attention shift. Neural networks based on synchronous oscil...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02
Inventor 段立娟房法明乔元华王海丽苗军吴春鹏
Owner BEIJING UNIV OF TECH
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