基于YOLOv7的奶牛行为识别方法研究

doi:10.19754/j.nyyjs.202406150010

摘要/Abstract

摘要： 为了实现适合大规模奶牛养殖环境下的无接触、高精度奶牛行为识别和自动化管理，本研究提出一种基于YOL07网络模型的奶牛行为识别方法，将牧场本地摄像头所采集的视频分帧处理，去除冗余图像后，通过标注，Mosaic数据增强处理得到440幅标签数据，用于对Y0L0v7模型进行训练及优化以实现奶牛行为的准确识别。实验结果表明，在训练轮次为150次时，模型对进食、躺卧和活动3类行为检测的平均精度均值达到 98.7%;对进食、站立、行走和躺卧4类行为检测的平均精度均值达到89.9%；相较Y0L0v5提高了1.5%，为实现畜禽智能化养殖提供支持。

中图分类号:

. 基于YOLOv7的奶牛行为识别方法研究[J]. 农业与技术, 2024, 44(11): 39-43.

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