Plant leaf pest identification method based on improved convolutional neural network

A convolutional neural network and plant leaf technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of large model parameters, long convergence time, low recognition accuracy, etc., and achieve simplified model parameters, The effect of improving accuracy and robustness

Pending Publication Date: 2020-08-21
空间信息产业发展股份有限公司
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Problems solved by technology

[0005] In view of the above-mentioned deficiencies in the prior art, the method for identifying plant leaf diseases and insect pests based on the improved convolutional neural network provided by the present invention solves the problems of long convergence time, large model parameters and low recognition accuracy in the training of existing plant disease and insect pest identification models.

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  • Plant leaf pest identification method based on improved convolutional neural network
  • Plant leaf pest identification method based on improved convolutional neural network
  • Plant leaf pest identification method based on improved convolutional neural network

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[0035] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0036] Such as figure 1 As shown, a method for identifying plant leaf diseases and insect pests based on an improved convolutional neural network includes the following steps:

[0037] S1. Collect original image data of different plants, including leaf images of diseases and insect pests and images of healthy leaves;

[0038] S2. Preprocessing the collected raw image data, constructing an image sample data set, and dividin...

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Abstract

The invention discloses a plant leaf pest identification method based on an improved convolutional neural network. According to the method, an improved AlexNet network model is provided, a convolutional neural network model combining batch normalization and global pooling is adopted to recognize various leaf diseases and insect pests, the improved model is greatly optimized in training time and memory requirements, model parameters are simplified, and meanwhile, the generalization ability of the model is also improved; according to the invention, the trained improved AlexNet feature network isused as a plant disease and insect pest identification model, so that the accuracy of plant leaf disease and insect pest identification is improved, the robustness is better, different diseases and insect pests of various plant leaves can be identified, and resources and time required by model training are reduced.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a method for identifying plant leaf diseases and insect pests based on an improved convolutional neural network. Background technique [0002] In recent years, the global climate has intensified and deteriorated, and the frequency and severity of agricultural meteorological disasters and pests and diseases in my country have increased, which greatly threatens my country's food security. As the ecological environment becomes more and more fragile, the phenomenon of crop diseases and insect pests is becoming more and more serious. Due to the decline in the quality of the plant growth environment, the spread of diseases and insect pests has been accelerated. Only by timely obtaining and identifying information on crop diseases and insect pests can effective control measures be taken. Although the use of chemical pesticides can control Plant diseases, but due to...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V20/20G06N3/045
Inventor 李潇熊洋
Owner 空间信息产业发展股份有限公司
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