Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep.

Kaler, Jasmeet; Mitsch, Jurgen; Vázquez-Diosdado, Jorge A; Bollard, Nicola; Dottorini, Tania; Ellis, Keith A

Kaler, Jasmeet; Mitsch, Jurgen; Vázquez-Diosdado, Jorge A; Bollard, Nicola; Dottorini, Tania; Ellis, Keith A.

Affiliation

Kaler J; School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire LE12 5RD, UK.
Mitsch J; Advanced Data Analysis Centre, Digital Research Service, University of Nottingham, Nottingham NG8 1BB, UK.
Vázquez-Diosdado JA; School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire LE12 5RD, UK.
Bollard N; School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire LE12 5RD, UK.
Dottorini T; School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire LE12 5RD, UK.
Ellis KA; Internet of Things Systems Research, Intel Labs, Leixlip W23 CX68, Ireland.

R Soc Open Sci ; 7(1): 190824, 2020 Jan.

Article de En | MEDLINE | ID: mdl-32218931

Mots clés

behaviour; lameness; machine learning; precision livestock farming; sensor; signal processing

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Diagnostic_studies / Guideline Langue: En Journal: R Soc Open Sci Année: 2020 Type de document: Article Pays d'affiliation: Royaume-Uni Pays de publication: Royaume-Uni

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