Description
This dataset accompanies the paper "Towards Self-Supervision for Video Identification of Individual Holstein-Friesian Cattle: The Cows2021 Dataset" at: https://arxiv.org/abs/2105.01938
It consists of three components: (a) Detection and localisation, (b) Identification, and (c) Weights.
For an overview of this dataset, refer to Section 2 in the paper.
For any queries, contact the corresponding author in the paper.
For the accompanying source code, check out https://github.com/Wormgit/Cows2021 in the paper.
It consists of three components: (a) Detection and localisation, (b) Identification, and (c) Weights.
For an overview of this dataset, refer to Section 2 in the paper.
For any queries, contact the corresponding author in the paper.
For the accompanying source code, check out https://github.com/Wormgit/Cows2021 in the paper.
| Date made available | 15 Jun 2021 |
|---|---|
| Publisher | University of Bristol |
Keywords
- Pattern Recognition
- Computer Vision
- Animal Biometrics
Research output
- 1 Chapter in a book
-
Label a Herd in Minutes: Individual Holstein-Friesian Cattle Identification
Gao, J., Burghardt, T. & Campbell, N. W., 13 Apr 2022, (Accepted/In press) 21st International Conference on Image Analysis and Processing Workshop (ICIAPW) on Learning in Precision Livestock Farming (LPLF). (Lecture Notes in Computer Science ).Research output: Chapter in Book/Report/Conference proceeding › Chapter in a book
Student theses
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Reducing the Individual Labelling Effort of Holstein-Friesian Cattle with Deep Learning
Gao, J. (Author), Campbell, N. W. (Supervisor) & Burghardt, T. (Supervisor), 10 Dec 2024Student thesis: Doctoral Thesis › Doctor of Philosophy (PhD)
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