作者
Juan Rodríguez Alvarez, Mauricio Arroqui, Pablo Mangudo, Juan Toloza, Daniel Jatip, Juan M Rodríguez, Alfredo Teyseyre, Carlos Sanz, Alejandro Zunino, Claudio Machado, Cristian Mateos
发表日期
2018/12/1
期刊
Computers and electronics in agriculture
卷号
155
页码范围
12-22
出版商
Elsevier
简介
BCS (“Body Condition Score”) is a method used to estimate body fat reserves and accumulated energy balance of cows. BCS heavily influences milk production, reproduction, and health of cows. Therefore, it is important to monitor BCS to achieve better animal response, but this is a time-consuming and subjective task performed visually by expert scorers. Several studies have tried to automate BCS of dairy cows by applying image analysis and machine learning techniques. This work analyzes these studies and proposes a system based on Convolutional Neural Networks (CNNs) to improve overall automatic BCS estimation, whose use might be extended beyond dairy production.
The developed system has achieved good estimation results in comparison with other systems in the area. Overall accuracy of BCS estimations within 0.25 units of difference from true values was 78%, while overall accuracy within 0.50 …
引用总数
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JR Alvarez, M Arroqui, P Mangudo, J Toloza, D Jatip… - Computers and electronics in agriculture, 2018