INVESTIGADORES
ZUNINO SUAREZ Alejandro Octavio
congresos y reuniones científicas
Título:
Body Condition Estimation on Cows from 3D Images Using Convolutional Neural Networks
Autor/es:
RODRIGUEZ ALVAREZ, J.; ARROQUI, M.; MANGUDO, P.; TOLOZA, J.; JATIP, D.; RODRIGUEZ, J. M.; ZUNINO, A.; MACHADO, C.; MATEOS, C.
Lugar:
Montevideo
Reunión:
Conferencia; The 1st International Conference on Agro Big Data and Decision Support Systems in Agriculture; 2017
Institución organizadora:
Red Iberoamericana de Agro-Bigdata y DSS para un sector agropecuario sostenible
Resumen:
BCS ("Body Condition Score") is a method 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. It 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 to use a method based on Convolutional Neural Networks (CNNs) to improve overall automatic BCS estimation and extending its use beyond dairy production.
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