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.
Original language | English |
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Number of pages | 2 |
Publication status | Published - 2 Sept 2022 |
Event | European Conference on Precision Livestock Farming: International Conference on Precision Dairy Farming - Vienna, Austria Duration: 29 Aug 2022 → 2 Sept 2022 |
Conference
Conference | European Conference on Precision Livestock Farming |
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Country/Territory | Austria |
City | Vienna |
Period | 29/08/22 → 2/09/22 |
Keywords
- cow identification
- behavioural analysis
- convolutional neural network