Litchi disease and insect pest identification method based on deep learning

Abstract

Aiming at the limitation of the prior art, the invention provides a litchi disease and insect pest identification method based on deep learning. According to the method, a deep learning training result is applied, various litchi diseases and insect pests can be automatically identified, and the problems of low efficiency, poor identification effect and the like of a traditional artificial disease and insect pest identification method are solved; according to a litchi disease and insect pest recognition model used in the scheme, an attention mechanism SimAM is introduced on the basis of a lightweight convolutional neural network ShuffleNetV2, an activation function Hardswitch is used, and a Dropout regularization method is adopted in a full connection layer; the litchi disease and insect pest recognition model can effectively extract important features, suppress interference of non-important features and improve network classification recognition performance, the number of network model parameters is not additionally increased, and storage and calculation expenses of the model are reduced.

Description

technical field [0001] The present invention relates to the technical field of agricultural pest identification, in particular to the application of deep learning and image recognition technology in the technical field of agricultural pest identification, and more specifically, to a method for identifying litchi pests based on deep learning. Background technique [0002] As one of the most important economic forest fruit trees in South my country, litchi has high medicinal value and is known as the "king of fruits". With the large-scale planting of litchi and the increasing number of cultivated varieties, the occurrence of litchi diseases and insect pests is also becoming more and more serious. Litchi pests and diseases not only have a wide variety, but also have a long disease cycle and difficult control, which seriously affect the quality and yield of litchi fruit. [0003] The existing identification method of litchi pests and diseases is mainly through the detection and...

AI Technical Summary

Problems solved by technology

[0005] At present, there are still many problems to be solved in the existing litchi pest identification technology: for example, there is still a lack of large-scale and complete image data sets of litchi pests and diseases; The ability to transform images is weak, the feature extraction ability of pest images is poor, and the established identification model of litchi pests is not effective.

Therefore, the prior art still has certain limitations

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