农作物漏苗检测技术研究综述OA

Seedling missing is a common issue in crop planting.It directly damages the crop population structure,re-duces resource utilization efficiency,and affects the final yield,posing a significant threat to food security and agricultur-al economic benefits.Based on the relevant research results of crop seedling missing detection in recent years,this paper conducts a review from two core dimensions:the necessity of seedling missing detection and detection methods.Firstly,it analyzes the impacts of the seedling missing problem on food security,economic benefits,and agricultural production efficiency,clarifying the urgent need for detection.Subsequently,it systematically sorts out the principles,application scenarios,and performance differences of three major types of technologies—traditional manual detection,machine vi-sion detection,and near-ground remote sensing detection—with a focus on expounding the advantages of the integrated technology of deep learning and UAV(Unmanned Aerial Vehicle)remote sensing in complex field environments.The research shows that the near-ground remote sensing detection technology driven by deep learning is the main develop-ment direction to solve the problem of seedling missing in large-scale farmland.At the same time,it points out the shortcomings of current technologies in multi-crop adaptability and robustness in complex environments,providing ref-erences for subsequent research.