关键词: 深度卷积神经网络, 病害识别, 智能手机, 智能识别系统, Socket网络

Abstract: In view of the difficulties of farmers and grassroots plant protection personnel in identifying crop diseases, the identification model is established by using VGG16 and Resnet50 for 18 crop diseases of apple, corn, grape and tomato as the research object. Through data pretreatment, data enhancement, model parameter optimization and model cross validation, the single crop multidisease identification and multi crop multidisease identification models are constructed. The performance comparison results show that VGG16 has better recognition performance than Resnet50, and the recognition accuracy of VGG16 model is more than 96%. After analyzing the VGG16 recognition model, it is found that the recognition performance of the single crop multidisease identification model has the best recognition performance. Therefore, based on the method of establishing single crop multidisease identification model, combined with smart phone, Web technology and network programming technology, this paper is proposed to develop an intelligent identification system of crop diseases. The system can provide users with accurate identification results, disease knowledge and prevention methods. The Socket network service of the system can be used as an independent module to provide a unified interface for crop disease identification for agricultural robots, intelligent agricultural machinery, unmanned aerial vehicle, agricultural expert systems, and so on. This study can provide technical support for the informatization and intellectualization of agricultural plant protection.

Key words: deep convolutional neural network, recognition of crop disease, smart phone, intelligent recognition system, Socket network