现代信息科技2024，Vol.8Issue(16)：127-130,135,5.DOI:10.19850/j.cnki.2096-4706.2024.16.027
基于ResNet50的水稻病虫害识别
Identification of Rice Pests and Diseases Based on ResNet50
摘要
Abstract
In order to accurately identify rice pests and diseases,8 types of rice pests and diseases images and health rice images are collected,which are used to construct a rice pests and diseases dataset.The Residual Network ResNet50 is used for identification of rice pests and diseases,and Transfer Learning and NonLocal Attention Mechanisms are introduced on the basis of the original model.The experimental results show that the accuracy,precision,recall,and F1-score of the improved model have reached 99.12％,99.31％,99.27％,and 99.28％,respectively,which are 2.92％,2.91％,4.05％,and 3.60％higher than the original model.Compared with models DenseNet121,Inception V3,ShuffleNet V2,MobileVit-small and ResNext50,the improved model has at least 2 percentage points higher on accuracy,precision,recall,and F1-score.The experiment verifies the effectiveness of the proposed model,which can accurately identify these types of rice pests and diseases.关键词
水稻病虫害/ResNet50模型/迁移学习/NonLocal注意力机制Key words
rice pests and diseases/ResNet50 model/Transfer Learning/NonLocal Attention Mechanism分类
信息技术与安全科学引用本文复制引用
丁士宁..基于ResNet50的水稻病虫害识别[J].现代信息科技,2024,8(16):127-130,135,5.基金项目
信阳农林学院青年教师科研基金项目:基于深度学习的水稻叶片病害预防检测研究(QN2021057) （QN2021057）
