Crop disease identification method and system based on DCGAN and RDN

An identification method and crop disease technology, applied in the field of agricultural informatization and plant protection, can solve the problems of difficult data collection, low practical application value, and large amount of disease data
CN112861752AActive Publication Date: 2021-05-28NORTHEAST AGRICULTURAL UNIVERSITY
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
NORTHEAST AGRICULTURAL UNIVERSITY
Publication Date
2021-05-28

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Abstract

The invention relates to a crop disease identification method and system based on DCGAN and RDN, and belongs to the field of agricultural informatization and plant protection, the method comprises the following steps: firstly, carrying out data collection, including a data set disclosed by a network and manually collected data, then, guaranteeing the accuracy and distribution balance of a training data set through the technologies of data visualization, data cleaning, DCGAN data generation and the like; dividing the processed data according to the proportion of 60% of a training set, 20% of a verification set and 20% of a test set; according to the method, a deep residual network (RDN) recognition model is constructed, and after model training parameters are set, a training set and a verification set are loaded for model training; and finally, the trained model is applied to a crop leaf disease identification system for crop disease prediction, and crop disease categories and probabilities are returned by the system. According to the method, various diseases of various crops can be recognized, and particularly, the recognition accuracy under the condition of uneven sample distribution can be improved.
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Description

technical field

[0001] The invention relates to the fields of agricultural informatization and plant protection, in particular to a crop disease identification method and system based on the combination of DCGAN and RDN. In particular, it relates to a recognition method and system that utilizes DCGAN technology for data enhancement and combines RDN algorithm to improve detection accuracy under the condition of uneven distribution of large-scale crop leaf training data. Background technique

[0002] 1. Professional terminology:

[0003] (1) DCGAN. DCGAN is the abbreviation of Deep Convolutional Generative Adversarial Networks (Deep Convolutional Generative Adversarial Networks). The present invention mainly uses DCGAN technology for data enhancement, which is used to expand training data, so as to enhance the generalization ability of the deep learning network and increase the accuracy of recognition.

[0004] (2) Deep Residual Network. A deep learning model, please refer ...

Claims

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