Classification and identification of citrus pests based on InceptionV3 convolutional neural network and migration learning

As one of the origins of citrus in the world, China has a large number of excellent citrus resources and mature cultivation techniques. Pests and diseases have become an important constraint on citrus harvest and quality. At present, deep learning has been widely used in many fields, and its application in agricultural research is gradually becoming mature. The use of deep learning convolutional neural networks to identify citrus pests is an effective and high-discrimination recognition technology. In this paper, based on a small amount of self-collected citrus pests dataset, including Blowing scale, Moth, Starscream, Star beetle, Citrus fruit fly, a total of 5 common pests and diseases, and propose a combination of Inceptionv3 network feature extraction model and migration learning According to the classification and recognition method, the final recognition accuracy can reach 96.81%.