计算机与数字工程2024，Vol.52Issue(2)：554-558,621,6.DOI:10.3969/j.issn.1672-9722.2024.02.046
基于AlexNet的农作物病虫害识别研究
Research on Crop Pest and Disease Identification Based on AlexNet
摘要
Abstract
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.关键词
病虫害识别/AlexNet/图像识别/卷积神经网络Key words
identification of pests and diseases/AlexNet/image recognition/convolutional neural network分类
信息技术与安全科学引用本文复制引用
张娜,刘坤,杨国栋..基于AlexNet的农作物病虫害识别研究[J].计算机与数字工程,2024,52(2):554-558,621,6.基金项目
气候适应型城市重点实验室项目(编号:SLSY2019031) （编号:SLSY2019031）
商洛学院科研项目(编号:19SKY009)资助. （编号:19SKY009）
