使用摄像头和深度学习模型YOLOv12的自动检测乳母山羊的不对称乳头
Kacper Libera1, Maxime A M Pals2, Yvette de Geus3
1Institute for Risk Assessment Sciences (IRAS), Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, the Netherlands.
Journal of dairy science
|February 6, 2026
概括
一个新的计算机视觉模型可以自动检测乳母山羊的乳头不对称性,有助于早期检测乳腺炎. 这种自动化解决方案可以改善乳健康监测和动物福利.
科学领域:
- 兽医医学 兽医医学 兽医医学
- 计算机科学 计算机科学
- 动物科学动物科学
背景情况:
- 乳牛山羊的阴茎不对称是阴茎炎症 (乳腺炎) 的关键指标.
- 手动监测乳腺不对称是劳动密集型的,对于大群体来说是不切实际的.
- 需要自动化解决方案,以有效管理乳山羊的乳腺健康状况.
研究的目的:
- 开发和验证一个定制的计算机视觉模型,用于检测乳母山羊的乳腺不对称.
- 提供一个自动化工具,用于在挤奶期间定期监测乳房健康状况.
主要方法:
- 收集并注释了4,321张山羊的图像和373张背景图像.
- 训练了一个计算机视觉模型 (Udder_Asymmetry_Model),使用一个分为训练,验证和测试子集的数据集.
- 使用平均平均精度 (mAP) 度量 (mAP50和mAP50-95) 评估模型性能.
主要成果:
- 在测试数据集上, Udder_Asymmetry_Model 实现了令人满意的性能.
- 在50%重叠 (mAP50) 的平均精度为0.891 (95% CI:0.869-0.912).
- 在更严格的局部化 (mAP50-95) 中,平均精度为0.766 (95% CI:0.747-0.789).
结论:
- 使用计算机视觉,可以自动检测乳母山羊的阴茎不对称.
- 这项技术可以加强乳健康监测,改善动物福利和牛奶质量.
- 开发的模型为大型乳山羊养殖场提供了实用解决方案.
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