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Updated: Jan 16, 2026

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Evaluation of Auditory Brainstem Response in Chicken Hatchlings
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开发一种工具,用于检测养肉的口呼吸
Yali Ma1,2, Yongmin Guo1, Bin Gao1,2
1Key Laboratory of Smart Breeding (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Tianjin 300384, China.
Animals : an open access journal from MDPI
|September 27, 2025
概括
通过改进的YOLOv8n物体检测方法,检测肉的热应激变得更加容易. 这种先进的系统准确地识别出喘息,改善了动物福利监测和管理.
科学领域:
- 动物科学 动物科学
- 计算机视觉 计算机视觉
- 农业工程 农业工程
背景情况:
- 在肉中,张开嘴巴的喘息信号表明热量压力和福利问题.
- 在拥挤的环境中检测喘息是很困难的,因为小目标大小,闭塞,和背景杂乱.
研究的目的:
- 开发一种增强的物体检测方法,以准确识别肉喘息.
- 改善对肉热应激和福利的监测.
主要方法:
- 使用轻量级YOLOv8n框架与P2检测头用于小目标识别.
- 集成的空间到深度分组卷积 (SGConv) 用于细粒度特征提取.
- 采用双向特征金字塔网络 (BIFPN) 和挤压激发 (SE) 道关注,以增强特征表示和降噪.
主要成果:
- 在独立的测试组中达到0.92 mAP@50和在无泄漏的再训练中达到0.927 mAP@50.
- 与基线YOLO模型相比,表现出显著的性能改善.
- 证实了强大的通用性和实时性能,用于实际应用.
结论:
- 增强的YOLOv8n方法为智能肉福利监测提供了一个实用的解决方案.
- 这项技术有助于有效地管理热应激,并改善动物福祉.
- 可通用性的双重验证确保了在不同农业环境中的可靠性.
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