摘要
基于卷积神经网络的图像识别技术已经逐渐运用在了日常的农业生产中,并且在农产品的分类、鉴别等方面有着重大意义。论文结合具体的农业生产,介绍了目前卷积神经网络的常见模型结构及其应用方式,发现了现有模型的不足之处,并提出具有针对性的发展方向建议。
Image recognition technology based on convolutional neural network has been gradually used in daily agricultural production,and has great signifi cance in the classifi cation and identifi cation of agricultural products.Combined with specific agricultural production,the paper introduces the current common model structure and application methods of convolutional neural networks,fi nds the shortcomings of existing models,and proposes targeted development directions.
作者
孙思濂
SUN Silian(Beijing University of Chemical Technology,Beijing 100029)
出处
《软件》
2020年第11期173-175,共3页
Software
关键词
卷积神经网络
图像识别
农产品
convolutional neural network
image recognition
agricultural products
