智能化农业装备学报（中英文）2026，Vol.7Issue(1)：43-51,9.DOI:10.12398/j.issn.2096-7217.2026.01.005
基于GMA-YOLO11n的黄羽肉鸡行为多目标检测方法研究
Multi-objective monitoring method of yellow-feathered broiler behavior based on GMA-YOLO11n model
摘要
Abstract
Timely identification of abnormal conditions in broiler chickens through routine inspections is a crucial means to improve the efficiency of intensive poultry farming management.In intensive poultry farming,computer vision-based inspection technologies outperform traditional manual methods in both accuracy and efficiency,showing significant potential for development.However,in large-scale farms,challenges such as multi-scale targets and occlusion pose considerable difficulties for models.To address these issues,this study proposes an improved object detection method,termed GMA-YOLO11n(GSConv and multi-scale attention YOLO11n),based on the YOLO11n(you only look once)framework.Specifically,a GSConv lightweight convolution module is introduced into the Backbone to reduce computational complexity,and a high-resolution feature layer of 160×160 is added through multi-scale feature fusion to enhance the detection of small-scale and densely distributed targets.In addition,a squeeze-and-excitation(SE)channel attention module is incorporated before multi-scale feature inputs to strengthen the representation of key features.Experimental results demonstrate that the proposed model can effectively perform multi-class detection of daily behaviors,including drinking,feeding,and walking,as well as abnormal states of broiler chickens.The model achieves mean average precision values of 93.87%and 90.45%on Dataset I and Dataset Ⅱ,respectively,both outperforming the baseline model,while maintaining an inference speed that satisfies practical video inspection requirements.关键词
黄羽肉鸡/行为检测/YOLO11n/注意力机制/多尺度特征Key words
yellow-feathered broilers/behavior detection/YOLO11n/attention mechanism/multi-scale features分类
农业科技引用本文复制引用
陈虹菲,王孙缘,于佳琪,刘俊岭,肖茂华,钱燕,邹修国..基于GMA-YOLO11n的黄羽肉鸡行为多目标检测方法研究[J].智能化农业装备学报（中英文）,2026,7(1):43-51,9.基金项目
江苏省国际合作项目(BZ2023013) （BZ2023013）
国家重点研发子课题(2024YFD200030204) Jiangsu Provincial International Cooperation Project(BZ2023013) （2024YFD200030204）
Sub-project of the National Key Research and Development Program of China(2024YFD200030204) （2024YFD200030204）
