河南农业科学2026，Vol.55Issue(3)：19-27,9.DOI:10.15933/j.cnki.1004-3268.2026.03.003
深度学习在作物病害识别方面的研究进展
Research Progress of Deep Learning in Crop Disease Detection
摘要
Abstract
In recent years,with the rapid development of computer vision technology,intelligent disease recognition systems based on digital image processing have demonstrated remarkable application potential in early diagnosis and precise control of crop diseases due to their efficiency and accuracy.This paper systematically reviews research progress in deep learning techniques for crop disease recognition.Through a comparative analysis with traditional machine learning methods,it highlights the technical advantages and application limitations of deep learning algorithms in disease feature extraction and classification.Furthermore,the paper analyzes the comprehensive technical workflow of deep learning in crop disease recognition and enumerates application cases utilizing mainstream network architectures.On this basis,the paper discusses key technical challenges faced by deep learning applications for crop disease recognition in complex field environments and provides perspectives on future research directions.The aim is to provide theoretical foundation and technical support for promoting the practical application of intelligent early warning and precise recognition technologies for crop diseases in modern agricultural production systems.关键词
深度学习/作物病害识别/计算机视觉/智能诊断/农业信息化Key words
Deep learning/Crop disease recognition/Computer vision/Intelligent diagnosis/Agricultural informatization分类
农业科技引用本文复制引用
沈川,李夏..深度学习在作物病害识别方面的研究进展[J].河南农业科学,2026,55(3):19-27,9.基金项目
陕西省科技厅青年科技新星项目(2024ZC-KJXX-056) （2024ZC-KJXX-056）
陕西省教育厅青年创新团队科研计划项目(23JP001) （23JP001）
陕西省科技厅自然科学基础研究计划一般项目(2025JC-YBMS-213) （2025JC-YBMS-213）
