Research on Crop Pest and Disease Identification Based on AlexNet
Detection and identification of the symptoms of crop diseases and insect pests,so that people can accurately and timely formulate control plans and take measures to effectively reduce the occurrence of diseases and insect pests,which is a prereq-uisite for ensuring good growth of crops.In this paper,a crop pest identification based on AlexNet is proposed.First,the collected images of pests and diseases and healthy leaves are archived and classified,then the established data set is preprocessed by size nor-malization and data enhancement,and finally the AlexNet model is used to train the training set.The experiment shows that the ac-curacy rate can reach 96.93%after 5 times of training,and the method can complete the task of crop pest identification.Convolution-al neural network identification technology will become an important way to identify crop diseases and insect pests in the future,which is of great significance to the future development of precision agriculture and modern agriculture.
identification of pests and diseasesAlexNetimage recognitionconvolutional neural network
国家科技期刊平台
NSTL
万方数据
