Classification of broiler behaviours using triaxial accelerometer and machine learning

Author:

Yang X.,Zhao Y.,Street G.M.,Huang Y.,Filip To S.D.,Purswell J.L.

Funder

Mississippi State University

Publisher

Elsevier BV

Subject

Animal Science and Zoology

Reference47 articles.

1. Ali, A., Siegford, J., 2018. An approach for tracking directional activity of individual laying hens within a multi-tier cage-free housing system (aviary) using accelerometers. In Proceedings of 11th International Conference on Methods and Techniques in Behavioral Research, 5-8 June 2018, Manchester, UK, pp. 176–180.

2. Using a three-axis accelerometer to identify and classify sheep behaviour at pasture;Alvarenga;Applied Animal Behaviour Science,2016

3. Comparison of classification algorithms to predict outcomes of feedlot cattle identified and treated for bovine respiratory disease;Amrine;Computers and Electronics in Agriculture,2014

4. Using 3D vision camera system to automatically assess the level of inactivity in broiler chickens;Aydin;Computers and Electronics in Agriculture,2017

5. Application of a fully automatic analysis tool to assess the activity of broiler chickens with different gait scores;Aydin;Computers and Electronics in Agriculture,2010

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