Coarse cereal crop disease and insect pest detection method based on deep learning

A technology of deep learning and detection methods, applied in neural learning methods, structured data retrieval, biological neural network models, etc., can solve problems such as impact, and achieve the effect of simplifying the analysis process

Pending Publication Date: 2022-07-08
CHENGDU UNIV
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Problems solved by technology

[0004] In order to solve the technical problems in the above-mentioned prior art, the present invention provides a method for detecting pests and diseases of miscellaneous grain crops based on deep learning. and factors such as fatigue

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  • Coarse cereal crop disease and insect pest detection method based on deep learning

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[0043] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of the present application, but not all of the embodiments. The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Thus, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, all other embodim...

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Abstract

The invention relates to the technical field of cereal crop disease and insect pest recognition, in particular to a deep learning-based cereal crop disease and insect pest detection method, which comprises the following steps of: 1, establishing a disease and insect pest project database and a normal cereal crop model database; step 2, acquiring a to-be-identified field coarse cereal crop image based on a camera; step 3, preprocessing the obtained on-site coarse cereal crop image; 4, establishing a deep learning recognition model; 5, recognizing the preprocessed coarse cereal crop image through a deep learning recognition model; and step 6, the human-computer interaction interface displays an identification result. Calculation and analysis are carried out through the deep learning recognition model to obtain the disease and pest types of the coarse cereals; therefore, the problem that artificial sensory judgment is easily influenced by factors such as emotion, health and fatigue is effectively avoided.

Description

technical field [0001] The present invention relates to the technical field of identification of plant diseases and insect pests, in particular to a method for detecting plant diseases and insect pests based on deep learning. Background technique [0002] Multigrain crops usually refer to grain and soybean crops other than the five major crops of rice, wheat, corn, soybean and potato. There are mainly: sorghum, millet, buckwheat, oats, etc., which are characterized by short production period, small planting area, special planting area and low yield, and are generally rich in nutrients. [0003] At present, the problem of pests and diseases is one of the main reasons that seriously affect the agricultural production in my country. At present, the detection methods of pests and diseases are mainly artificial sensory judgment and physical and chemical detection. Artificial sensory judgment is easily affected by some subjective factors such as emotion, health, fatigue, etc.; wh...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/10G06V10/44G06V10/56G06V10/764G06K9/62G06V10/82G06F16/22G06N3/04G06N3/08
CPCG06F16/2228G06N3/08G06N3/045G06F18/2431Y02A40/10
Inventor 蒲强
Owner CHENGDU UNIV
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