Artificial calf weaning strategies and the role of machine learning: A review

Sukumar Katamreddy, D. Riordan, P. Doody
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引用次数: 3

Abstract

Research in Machine Learning has increased dramatically over the past couple of decades, with applications greatly benefitting industry. These applications vary widely in the fields of space exploration technologies, transportation, robotics, agriculture, animal husbandry, medicine and finance. However, the agricultural and animal husbandry related applications are relatively few when compared to other fields. This paper reviews the past and present calf weaning strategies mainly focussing on the incorporation of Machine Learning techniques in classifying the behavioural responses in cattle and makes an attempt to extend the scope of machine learning classification applications related to calf weaning. This review further discusses the integration of relevant sensors (sensor fusion), deep learning and the improvement of prediction accuracy.
人工犊牛断奶策略和机器学习的作用:综述
在过去的几十年里,机器学习的研究急剧增加,其应用使工业受益匪浅。这些应用在空间探索技术、交通运输、机器人、农业、畜牧业、医药和金融等领域有很大的不同。然而,与其他领域相比,农牧相关的应用相对较少。本文回顾了过去和现在的小牛断奶策略,主要集中在结合机器学习技术对牛的行为反应进行分类,并试图扩展与小牛断奶相关的机器学习分类应用范围。本文进一步讨论了相关传感器的集成(传感器融合)、深度学习和预测精度的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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