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A convolutional neural network-based human body cell protein automatic identification method and system

A technology of convolutional neural network and automatic identification system, which is applied in the field of automatic identification and system of human cell proteins based on convolutional neural network, to achieve the effect of accelerating scientific research progress

Active Publication Date: 2019-05-10
SHANDONG INSPUR SCI RES INST CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical task of the present invention is to provide a method and system for automatic identification of human cell proteins based on convolutional neural networks to solve how to use the convolutional neural network classifier in supervised learning to identify the protein category in the cells in the image, and then determine whether the cells are normal The problem

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  • A convolutional neural network-based human body cell protein automatic identification method and system
  • A convolutional neural network-based human body cell protein automatic identification method and system
  • A convolutional neural network-based human body cell protein automatic identification method and system

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Embodiment 1

[0065] as attached figure 1 As shown, the method for automatic recognition of proteins in human cells based on convolutional neural network of the present invention, the method steps are as follows:

[0066] S1. Data set preprocessing: make a data set according to the input format of the ProteinResNet32 model (residual convolutional neural network model), and set the protein order to determine, then

[0067] D={(x,y)|x∈R 512*512*4 , y=α 1*m};

[0068] Among them, D is the data set; R is the real number set; m is the number of protein categories; α 1*m is a 1*m category vector; x is a sample; y is a label; when the category of sample x contains the kth protein category, label y=α 1*m The value of the kth element of is 1, otherwise it is 0;

[0069] In the data set D, 70% of the samples are randomly selected according to the category as the training set, and the remaining 30% are used as the test set.

[0070] S2. Model implementation and training: According to the structu...

Embodiment 2

[0092] The human cell protein automatic recognition system based on the convolutional neural network of the present invention includes a data set preprocessing module, a model realization and training module, and a model deployment and continuous optimization module;

[0093] Among them, the data set preprocessing module is used to make a data set according to the input format of the ProteinResNet32 model (residual convolutional neural network model), and set the protein order to determine;

[0094] The model implementation and training module is used to implement the ProteinResNet32 model and train the ProteinResNet32 model; the model implementation and training module includes a model implementation module and a model training module;

[0095] The model implementation module is used to select the deep learning programming framework according to the structure of the ProteinResNet32 model and use the ReLU activation function to act on all convolutional layers and fully connecte...

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Abstract

The invention discloses a human body cell protein automatic identification method and system based on a convolutional neural network. The method belongs to the field of utilizing a computer vision scheme to automatically identify and classify medical microscope images. The technical problem to be solved by the invention is how to identify protein categories in cells in an image by using a convolutional neural network classifier in supervised learning. According to the adopted technical scheme, the method for automatically identifying the protein in the human cells based on the convolutional neural network comprises the following steps: S1, preprocessing a data set: making the data set according to the input format of a Protein ResNet 32 model, and setting a protein sequence to be determined; S2, model realization and training; and S3, model deployment and continuous optimization. And (2) a human body cell protein automatic identification system based on a convolutional neural network.The system comprises a data set preprocessing module, a model realization and training module and a model deployment and continuous optimization module.

Description

technical field [0001] The invention relates to the field of automatic recognition and classification of medical microscope images by using a computer vision scheme, in particular to a method and system for automatic recognition of human cell proteins based on a convolutional neural network. Background technique [0002] The convolutional neural network can learn the spatial features in the original data, and a feature representation learner can be formed by stacking different convolutional layers together. The learner learns the feature representation of the input data layer by layer from shallow to deep, and finally outputs a low-dimensional feature vector relative to the original data, which can be used as an input feature by the classifier to achieve correct classification of the original data. The convolutional neural network and the fully connected classifier are spliced ​​together to form a common convolutional neural network classifier, and the convolution kernel wei...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
Inventor 高岩姜凯于治楼
Owner SHANDONG INSPUR SCI RES INST CO LTD
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