Inclusion of features derived from a mixture of time window sizes improved classification accuracy of machine learning algorithms for sheep grazing behaviours-Reference-Cited by-同舟云学术

Inclusion of features derived from a mixture of time window sizes improved classification accuracy of machine learning algorithms for sheep grazing behaviours

Published:2020-12 Issue: Volume:179 Page:105857
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Hu Shuwen,Ingham Aaron,Schmoelzl Sabine,McNally Jody,Little Bryce,Smith Daniel,Bishop-Hurley Greg,Wang You-Gan,Li Yutao

Funder

Australian Research Council

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference24 articles.

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3. Bar, D., & Solomon, R. (2010, March 2-5). Rumination collars: What can they tell us. [Paper presentation]. The First North American Conference on Precision Dairy Management, Toronto, ON, Canada.

4. Predicting Lameness in Sheep Activity Using Tri-Axial Acceleration Signals;Barwick;Animals (Basel),2018

5. Identifying sheep activity from tri-axial acceleration signals using a moving window classification model;Barwick;Remote Sensing,2020

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