Crop pest control scheme recommendation system based on deep learning

A recommendation system and deep learning technology, applied in the field of crop pest control program recommendation system, can solve problems such as loss, limitation, and input information limit, and achieve accurate, excellent, stable and reliable results

Inactive Publication Date: 2017-11-07
CHONGQING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

Patent CN106841304A discloses a method of using infrared images to monitor crop diseases and comprehensively evaluate the degree of disease. This method is not sensitive to light, but it loses a lot of useful information in visible light, thus limiting the amount of input information
CN 104899547A discloses a method for diagnosing crop diseases based on feature extraction and semantic understanding. This method is limited by preset features, so unextracted features that are helpful for diagnosis may be lost

Method used

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  • Crop pest control scheme recommendation system based on deep learning
  • Crop pest control scheme recommendation system based on deep learning

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Embodiment Construction

[0023] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] Such as figure 1 As shown, a crop disease and pest control program recommendation system based on deep learning, including an image acquisition system, an image processing system, a crop disease and pest identification system, a crop disease and pest control system, and a crop disease and pest control effect information feedback system;

[0025] The image acquisition system is used to acquire images of crops, and transmit image information to the image processing system;

[0026] The image processing system denoises and normalizes the received image information to form training data, which is transmitted to the crop pest identification system;

[0027] Such as figure 2 As shown, the crop disease and pest identification system identifies relevant information of crops according to the received training data analysis, and uses it as ...

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Abstract

The invention relates to a crop pest control scheme recommendation system based on deep learning, and belongs to the field of agricultural modernization. The system comprises an image acquisition system, an image processing system, a crop pest identification system, a crop pest control system, a crop pest control effect information feedback system and a user feedback information authenticity identification system. An incremental learning method is adopted. The neural network structure is continuously optimized by the crop pest control system according to the information of the crop pest control effect information feedback system, and the crop names, the local weather records and the color images of the leaves are combined to act as the key information for pest identification so that the result is more stable and reliable and more accurate.

Description

technical field [0001] The invention belongs to the field of agricultural modernization, and relates to a deep learning-based recommendation system for crop disease and insect pest control schemes. Background technique [0002] Domestic research on agricultural expert systems began in the early 1980s. Due to some characteristics of my country's agriculture itself, such as low per capita agricultural water and soil resources, poor cultural quality of farmers, shortage of agricultural experts and scientific and technological personnel, etc., the development and application of agricultural expert systems have been widely valued from the beginning, and have become information Important aspects of technology application in agriculture. The state attaches great importance to the application of artificial intelligence technology in agriculture, and lists it as a key research project in the "Seventh Five-Year Plan" and "Eighth Five-Year Plan". And with the support of the National 8...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06Q50/02G06N3/04G06N3/08
CPCG06N3/08G06Q50/02G06T7/0012G06T2207/20084G06T2207/20081G06T2207/10024G06T2207/30004G06N3/045
Inventor 钱鹰王喜宾刘歆贾朝龙朱红军叶青青夏璨刘微微王茂瑞冯相辉孙惟智
Owner CHONGQING UNIV OF POSTS & TELECOMM
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