Low-cost tomato leaf disease identification method based on lightweight deep neural network

Abstract

The invention discloses a low-cost tomato leaf disease identification method based on a lightweight deep neural network, and the method comprises the following steps: collecting a tomato leaf image data set, expanding the collected tomato leaf image data set through a data set expansion method to obtain an expanded image database, and carrying out the preprocessing of the image data set; constructing an improved residual neural network recognition model, and inputting the preprocessed image data set into the improved residual neural network recognition model to complete the training of the model; and recognizing a to-be-detected picture to be actually detected by using the trained model. According to the invention, an improved residual neural network identification model is adopted; disease identification is carried out on tomato leaves through cooperation of separable multi-scale convolution module1 and module2. According to the method, the network width is expanded, the accuracy reaches a relatively high level, the occupied memory is relatively small, real-time identification of tomato diseases on a low-performance terminal can be realized, and the method can be popularized to crop disease identification of other similar application scenes.

Description

technical field [0001] The invention relates to the technical field of computer image processing, in particular to a low-cost tomato leaf disease identification method based on a lightweight deep neural network. Background technique [0002] my country is a large agricultural country, and the level of agricultural production is crucial to the country's economic construction and development. However, diseases are one of the main factors limiting crop cultivation. When crops are attacked by diseases, the yield of agricultural products will be greatly reduced in severe cases, which will bring huge losses to the agricultural economy. Therefore, early identification of diseases is extremely critical to choosing the right treatment method, and it has also become an important prerequisite for reducing crop losses and reducing the use of pesticides. Tomato is a vegetable with many diseases. Currently, there are more than 20 kinds of diseases that cause yield reduction or extinctio...

AI Technical Summary

Problems solved by technology

However, on the one hand, the deep neural network requires a large amount of data training set and requires precise labeling, which brings great difficulties to practical applications. On the other hand, it takes up a lot of computer memory and consumes a lot of computing resources, making it difficult to apply to low-cost terminal devices.

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