Cow identification network trained with similarity learning
Ulrichsen, Alexander and Murray, Paul and Marshall, Stephen and Lee, Brian and Rutter, Mark (2022) Cow identification network trained with similarity learning. In: European Conference on Precision Livestock Farming, 2022-08-29 - 2022-09-02.
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Abstract
Cow identification is a key phase in automated processing of cow video footage for behavioural analysis. Previous cow identification works have achieved up to 97.01% accuracy on 45 cows and 94.7% on datasets containing up to 200 cows. This paper presents new results from applying similarity learning to a cow identification Convolutional Neural Network on a group of 537 cows. Our method achieves identification accuracy of up to 99.3% and generalizes well to new cows, eliminating the need for retraining every time a new cow is added to the heard.
ORCID iDs
Ulrichsen, Alexander, Murray, Paul ORCID: https://orcid.org/0000-0002-6980-9276, Marshall, Stephen ORCID: https://orcid.org/0000-0001-7079-5628, Lee, Brian and Rutter, Mark;-
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Item type: Conference or Workshop Item(Paper) ID code: 83098 Dates: DateEvent2 September 2022Published11 April 2022AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering > Electrical apparatus and materials Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 08 Nov 2022 10:24 Last modified: 05 Sep 2024 00:30 URI: https://strathprints.strath.ac.uk/id/eprint/83098