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. (In Press)

[thumbnail of Ulrichsen-etal-ECPLF-2022-Cow-identification-network-trained-with-similarity]
Preview
 Text. Filename: Ulrichsen_etal_ECPLF_2022_Cow_identification_network_trained_with_similarity.pdf
Accepted Author Manuscript
License: Creative Commons Attribution-NonCommercial 4.0 logo
Download (639kB)| Preview

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 logoORCID: https://orcid.org/0000-0002-6980-9276, Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628, Lee, Brian and Rutter, Mark;
CORE (COnnecting REpositories)