All Outputs (2)

Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving Beyond Classification in Precision Livestock (2020)
Journal Article
Carslake, C., Vázquez-Diosdado, J. A., & Kaler, J. (2021). Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving Beyond Classification in Precision Livestock. Sensors, 21(1), 1-14. https://doi.org/10.3390/s21010088

Previous research has shown that sensors monitoring lying behaviours and feeding can detect early signs of ill health in calves. There is evidence to suggest that monitoring change in a single behaviour might not be enough for disease prediction. In... Read More about Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving Beyond Classification in Precision Livestock.

Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep (2020)
Journal Article
Kaler, J., Mitsch, J., Vázquez-Diosdado, J. A., Bollard, N., Dottorini, T., & Ellis, K. A. (2020). Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep. Royal Society Open Science, 7(1), Article 190824. https://doi.org/10.1098/rsos.190824

Lameness in sheep is the biggest cause of concern regarding poor health and welfare among sheep producing countries. Best practice for lameness relies on rapid treatment, yet there are no objective measures of lameness detection. Use of accelerometer... Read More about Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep.