Find in Library

[Purpose/Significance] Fruit tree diseases endanger the safety of agricultural production, and the use of artificial intelligence technologies to help fruit growers identify fruit tree diseases in a timely and accurate manner is of great significance to ensure safe agricultural production. [Method/Process] Using 10 000 fruit tree leaf diseased spots image data sets, through image enhancement methods such as rotation, pollution, noise enhancement, and cutting to improve the diversity of sample images; using the ResNet-50 deep convolutional network model to perform machine learning to obtain the fruit tree diseases identification model, and develop application software based on this model to provide online diagnostic services. [Results/Conclusions] The experimental results show that the average recognition rate of the four fruit tree diseases reached 92.9%, which has a better diagnostic effect compared with related research results.