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Pest and disease image generation method based on generative adversarial network

A technology for image generation and pest damage, applied in biological neural network models, character and pattern recognition, instruments, etc., can solve the problem of few sampling images of pest and disease images

Inactive Publication Date: 2017-08-04
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the defect of few sampling images of pest images in the prior art, and provide a method for generating pest images based on generative confrontation network to solve the above problems

Method used

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  • Pest and disease image generation method based on generative adversarial network
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Embodiment Construction

[0042] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0043] Such as figure 1 As shown, a method for generating images of diseases and insect pests based on generative confrontation network according to the present invention comprises the following steps:

[0044] The first step is to collect and preprocess the training images, collect several images as training images, and normalize the size of all training images to 256×256 pixels to obtain several training samples.

[0045] In the second step, the discriminant network and the generation network are constructed based on the deep convolutional neural network model. The deep convolutional neural network emphasizes the depth of the model structure, highlights the importance of feature learning, and can learn the essential features of the ...

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Abstract

The invention relates to a pest and disease image generation method based on a generative adversarial network. In the prior art, sampling images of pest and disease images are less. By using the method of the invention, the above defect is overcome. The method comprises the following steps of collecting and preprocessing trained images; based on a deep-convolution neural network model, constructing a discrimination network and a generation network; training the discrimination network and the generation network; and according to the trained generation network, generating the pest and disease images. In the invention, according to a few of existing pest and disease images, a lot of pest and disease images which are similar to a reality are generated, a sample image is provided for pest and disease image identification, and problems that the pest and disease images in an actual field are less and acquisition cost is high are solved.

Description

technical field [0001] The invention relates to the technical field of image generation, in particular to a method for generating images of diseases and insect pests based on generative confrontation networks. Background technique [0002] Pests and diseases are the enemies of crops. They occur throughout the growth period of crops and can cause a large reduction in crop yield. Effective identification of pests and diseases through software technology has become a research hotspot in the industry. However, the current pest diagnosis method based on image recognition requires a large number of pest image samples as the support of raw data. However, in practical applications, there are relatively few samples of existing images of pests and diseases, and the workload of collecting images of field diseases and insect pests is relatively difficult and large. [0003] Therefore, how to use a small number of existing pest images to realize the regeneration of pest images has becom...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/214
Inventor 张洁王儒敬宋良图谢成军余健李瑞陈红波陈天娇许桃胜宿宁
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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