现代信息科技2025，Vol.9Issue(1)：35-39,5.DOI:10.19850/j.cnki.2096-4706.2025.01.008
基于深度学习的鹰嘴桃病虫害监测技术研究
Research on Pest and Disease Monitoring Technology for Yingzui Peach Based on Deep Learning
摘要
Abstract
Aiming at the problems of low efficiency and complex operation of traditional disease identification methods,the pest and disease identification algorithm of Yingzui peach based on Deep Learning is proposed.Based on the ResNet50 network architecture,the algorithm uses the method of combining image recognition technology and Deep Learning to establish a high efficiency pest and disease monitoring system,which can quickly and accurately identify various types of pests and diseases.Firstly,a specialized dataset is established for 14 common pests and diseases of Yingzui peach in Lianping area of Heyuan.Secondly,the Deep Residual Network Model is used for training.Finally,the Graphical User Interface is developed using PyQt5 to realize the automatic diagnosis of pest and disease.This automatic diagnosis system is not only efficient and labor-saving but also environmentally friendly.It conforms to the development trend of smart agriculture and provides users with accurate control methods of pest and disease.关键词
图像识别技术/病虫害监测/深度学习/病虫害数据集/智慧农业/鹰嘴桃病虫害Key words
image recognition technology/pest and disease monitoring/Deep Learning/pest and disease dataset/smart agriculture/Yingzui peach pest and disease分类
通用工业技术引用本文复制引用
甘玉婉,曾静,周永福,李泽航,胡展羽,林焕伟..基于深度学习的鹰嘴桃病虫害监测技术研究[J].现代信息科技,2025,9(1):35-39,5.基金项目
广东省重点科研项目(2024ZDZX4089) （2024ZDZX4089）
广东省高校青年创新人才项目(2024KQNCX207) （2024KQNCX207）
广东省高校青年创新人才项目(2023KQNCX233) （2023KQNCX233）
