现代信息科技2025，Vol.9Issue(20)：27-34,8.DOI:10.19850/j.cnki.2096-4706.2025.20.006
面向无人机航拍目标检测的YOLO系列算法研究进展
Research Progress of YOLO Series Algorithms for UAV Aerial Photography Object Detection
摘要
Abstract
UAVs integrated with Object Detection technology leverage their aerial perspective and high mobility to provide significant flexibility for object localization and data collection.However,in practical applications,UAV aerial photography-based Object Detection faces challenges such as stringent real-time requirements,a high proportion of small objects,and complex image backgrounds,limiting its development and application.Therefore,designing algorithm models capable of effectively adapting to the characteristics of UAV aerial imagery is particularly important.Since its inception,the YOLO series algorithms have undergone multiple iterations.It achieves simultaneous object classification and localization via a single network forward pass,offering excellent real-time performance.This paper summarizes the research progress of the main versions of the YOLO series algorithms and presents their applications in UAV aerial photography-based Object Detection,aiming to provide a reference for subsequent research.关键词
无人机航拍/目标检测/YOLO/计算机视觉/小目标检测Key words
UAV aerial photography/Object Detection/YOLO/Computer Vision/small Object Detection分类
信息技术与安全科学引用本文复制引用
胡军,虞文鹏..面向无人机航拍目标检测的YOLO系列算法研究进展[J].现代信息科技,2025,9(20):27-34,8.基金项目
江西飞行学院校级一般项目(2024YB01) （2024YB01）
