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31 results about "Central neuron" patented technology

Motor neurons carry information from the central nervous system to organs, glands, and muscles. Sensory neurons send information to the central nervous system from internal organs or from external stimuli. Interneurons relay signals between motor and sensory neurons.

Automatic detection system for traditional-Chinese-medicine quality

The invention discloses an automatic detection system for the traditional-Chinese-medicine quality. Traditional-Chinese-medicine original images are collected, outlines of target areas are partitioned, the images are subjected to noise removing, a neural network PCNN corresponds to the images, central neuron corresponds to pixel points of the images, multi-wavelength LED lamps are illumed respectively, several LED lamps capable of motivating remarkable fluorescence signals are selected and alternately illumed, traditional-Chinese-medicine samples with fluorescence spectrums of 300 nm-1,100 nm are collected, the one-dimensional time-series signal characteristics of all two-dimensional images are extracted, characteristic information is stored, the airspace characteristics of traditional-Chinese-medicine microscopic images are extracted, and the traditional-Chinese-medicine quality is detected. According to the automatic detection system, the traditional-Chinese-medicine external parameters are synthetically evaluated with the electronic technology, the traditional-Chinese-medicine inherent quality is automatically detected by combing traditional-Chinese-medicine chemical-component content parameters, safety detection parameters and conventional detection parameters, the detection standard is objective and uniform, and accurate medicine making can be achieved.
Owner:YICHUN UNIVERSITY

Contour detection method based on non-classical receptive field space summation modulation

The invention aims at providing a contour detection method based on non-classical receptive field space summation modulation. The method comprises the steps that 1, a to-be-detected image subjected to grey-scale processing is input; 2, Gabor filtering is conducted on the to-be-detected image to obtain Gabor energy values of all pixel points in all directions; 3, a space summation modulation weight of a non-classical receptive field to a central neuron is calculated out; 4, modulation response of the non-classical receptive field to the central neuron on a distance weight is calculated out; 5, stimulating response of the central neuron to the non-classical receptive field is obtained through calculation; 6, stimulating response of the central neuron to combined modulation of a classical receptive field and the non-classical receptive field is obtained through calculation and serves as a corresponding contour value; 7, non-maximum suppression and double-threshold processing are conducted on the contour values of all the pixel points, and final contour values of all the pixel points are obtained. The contour detection method based on non-classical receptive field space summation modulation overcomes the defects that in the prior art, the simulation effect is poor, and the contour recognition rate is low and has the advantages of being good in simulation effect and high in contour recognition rate.
Owner:西安鑫柏泽文化传媒有限公司

Contour detection method based on non-classical receptive field and linear nonlinear modulation

The present invention provides a contour detection method based on a non-classical receptive field and linear nonlinear modulation. The method comprises: A, inputting an image to be detected through gray processing; B, performing Gabor filtering of the image to be detected to obtain the Gabor energy value of each direction of each pixel point; C, constructing X-cell and Y-cell simulation models in a retina ganglion cell; D, calculating and obtaining stimulating response of each central neuron through the non-classical receptive field corresponding to the X cell; E, calculating and obtaining the stimulating response of each central neuron through the non-classical receptive field corresponding to the Y cell; F, respectively calculating the stimulating response of central neurons of the X cell and the Y cell through the combined modulation of the classical receptive field and the non-classical receptive field, and performing addition of the stimulating response of central neurons of the X cell and the Y cell to take as a corresponding contour value; and G performing processing of the contour values of each pixel point to obtain a final contour value. The contour detection method based on the non-classical receptive field and the linear nonlinear modulation overcomes the defect that the contour recognition rate is low in the prior art, and has good simulation effect and high contour recognition rate.
Owner:GUANGXI UNIVERSITY OF TECHNOLOGY

Construction of neural stem cell derived tissue engineering spinal cord tissue

The invention relates to a neural stem cell derived tissue engineering spinal cord tissue for simulating a spinal cord tissue structure and main cell constituents. The neural stem cell derived tissue engineering spinal cord tissue is obtained by in-vitro culture and construction through a biological tissue engineering technology and a neural stem cell induced differentiation technology, and has a white matter like structure in the peripheral part and a grey matter like structure in the central part. CNTF (ciliary neurotrophic factor) gene modified oligodendrocyte precursor cells (OPCs) are planted in the white matter like structure; and NT-3 gene and receptor thereof TrkC gene modified neural stem cells (NSCs) are planted in the grey matter like structure. When being transplanted to a spinal cord complete transection injury site, the tissue engineering spinal cord tissue has favorable cell activity and can secrete neurotrophic factors to accelerate regeneration of spinal cord injured central neuron axons; and the tissue engineering spinal cord tissue can realize corresponding functions of oligodendrocytes and neurons, and serves as a neural information transfer relay to form a synaptic connection with regenerated nerve fibers so as to repair spinal cord injured neural circuits. The tissue engineering spinal cord tissue can also be used as an in-vitro model for neural pharmacology and neural development researches.
Owner:SUN YAT SEN UNIV

An automatic detection system for the quality of traditional Chinese medicine

The invention discloses an automatic detection system for the quality of traditional Chinese medicine, which collects the original image of traditional Chinese medicine, segments the outline of the target area, performs image denoising, corresponds the neural network PCNN to the image, and corresponds the central neuron to the pixel points of the image, respectively Brighten a single multi-wavelength LED lamp, select several LEDs that can stimulate significant fluorescent signals to light up in turn, collect the fluorescence spectrum of the Chinese medicine sample at 300nm‑1100nm, extract the one-dimensional time series signal characteristics of each two-dimensional image and store the characteristic information, and extract the traditional Chinese medicine The spatial characteristics of microscopic images are used to detect the quality of traditional Chinese medicines. The invention uses electronic technology to comprehensively evaluate the external parameters of traditional Chinese medicine, and automatically detects its inherent quality in combination with the parameters of chemical composition content, safety detection parameters and conventional detection parameters of traditional Chinese medicine. The detection standards are objective and unified, which is beneficial to accurate dispensing.
Owner:YICHUN UNIVERSITY

Visual computation multivariate connection model-based saliency contour perception method

The invention discloses a saliency contour perception method based on a visual calculation multivariate connection model. The visual calculation model with a multivariate connection characteristic is constructed. On the basis of LGN feedforward connection, LGN neuron sparse coding characteristics are simulated, a weight factor is added, preliminary texture suppression is achieved, and a primary sensing result of a contour is obtained; on the horizontal connection of the primary visual cortex, simulating a primary visual cortex windmill-like structure receptive field, and adjusting the discharge intensity of a central neuron based on the distance between neurons and the optimal orientation included angle; and on the feedback connection of the advanced visual cortex layer, simulating the hue perception characteristics of the advanced visual cortex layer, constructing a three-channel hue perception model containing surround suppression, and obtaining the response of the advanced visual cortex layer to an image target or structure. According to the invention, through the construction of the visual calculation model with the multi-element connection characteristic, the obtained contour can effectively highlight the main body target while suppressing the texture noise.
Owner:HANGZHOU DIANZI UNIV

Neural network situation prediction method based on dynamic k-means clustering

The neural network situation prediction method based on dynamic k-means clustering includes the following steps: 1) Collect basic network security data of a certain system, the data indicators are the number of hosts infected with network viruses, the number of tampered networks, the number of networks implanted with backdoors, The number of security incident reports, the number of counterfeit pages, and the number of security vulnerabilities and high-risk vulnerabilities are normalized for the basic network security data; 2) The normalized basic network security data is clustered using the dynamic k-means clustering algorithm Class, determine the RBF neural network central neuron parameters and the number N; 3) Use the normalized data to participate in RBF neural network training, calculate the RBF neuron width and determine the neuron output; 4) During the training process, the RBF The output weight of the neural network is encoded, and the PSO algorithm is used to obtain the optimal weight, which improves the accuracy of network situation prediction; 5) Use the trained RBF neural network to predict the network situation of a certain month, and compare it with the network situation evaluation value of the month Contrast, calculation error; it has the characteristics of high prediction accuracy.
Owner:XIAN UNIV OF POSTS & TELECOMM

Contour Detection Method Based on Spatial Sum Modulation of Nonclassical Receptive Fields

ActiveCN106033610BIn line with physiological characteristicsMaintain contour integrityImage analysisPhysical realisationCentral neuronSummation equation
The invention aims at providing a contour detection method based on non-classical receptive field space summation modulation. The method comprises the steps that 1, a to-be-detected image subjected to grey-scale processing is input; 2, Gabor filtering is conducted on the to-be-detected image to obtain Gabor energy values of all pixel points in all directions; 3, a space summation modulation weight of a non-classical receptive field to a central neuron is calculated out; 4, modulation response of the non-classical receptive field to the central neuron on a distance weight is calculated out; 5, stimulating response of the central neuron to the non-classical receptive field is obtained through calculation; 6, stimulating response of the central neuron to combined modulation of a classical receptive field and the non-classical receptive field is obtained through calculation and serves as a corresponding contour value; 7, non-maximum suppression and double-threshold processing are conducted on the contour values of all the pixel points, and final contour values of all the pixel points are obtained. The contour detection method based on non-classical receptive field space summation modulation overcomes the defects that in the prior art, the simulation effect is poor, and the contour recognition rate is low and has the advantages of being good in simulation effect and high in contour recognition rate.
Owner:西安鑫柏泽文化传媒有限公司
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