农业工程2026，Vol.16Issue(5)：37-46,10.DOI:10.19998/j.cnki.2095-1795.202512011
基于DW-YOLOv7-tiny的荠菜种子出芽检测方法
Detection method for shepherd's purse seed germination based on DW-YOLOv7-tiny
摘要
Abstract
To enhance efficiency and accuracy of germination detection for ultra-small seed and meet demand for automation,shepherd's purse seed were selected as research subject.Through shepherd's purse seed germination experiments'image analysis,a YOLOv7-tiny-based seed germination detection and recognition method was improved and designed to achieve rapid detection of shep-herd's purse seed germination,and detection experiments were conducted.Experimental results showed that YOLOv7-tiny achieved a germination discrimination accuracy of 92.7%for shepherd's purse seed,while improved DW-YOLOv7-tiny reached 96.2%.Compared to original data,parameter count and computational load were decreased by 3.32%and 4.35%,respectively.Model's accuracy,recall,and average precision mean increased by 3.5,2.5,and 1.8 percentage points,respectively.Model's weight file size was reduced by 1.0 MB,achieving greater lightweight performance while maintaining a detection speed of 121 f/s.These results demonstrate effective-ness of improved method,which is particularly suitable for rapid germination detection of ultra-small seeds like shepherd's purse in spe-cialized application scenarios.关键词
荠菜种子/发芽检测/深度学习/YOLOv7-tiny/图像处理/轻量化Key words
shepherd's purse seed/germination detection/deep learning/YOLOv7-tiny/image processing/light weight分类
农业科技引用本文复制引用
苏昭名,张还,杨然兵,潘志国,郭鑫雨,李耀,李鑫林..基于DW-YOLOv7-tiny的荠菜种子出芽检测方法[J].农业工程,2026,16(5):37-46,10.基金项目
海南省南繁育种全程机械化科研试验基地建设项目(10022GKSN247) （10022GKSN247）
