Exploring Cluster Analysis in Nelore Cattle Visual Score Attribution
Image and Video Processing
2024-03-13 v1 Computer Vision and Pattern Recognition
Machine Learning
Abstract
Assessing the biotype of cattle through human visual inspection is a very common and important practice in precision cattle breeding. This paper presents the results of a correlation analysis between scores produced by humans for Nelore cattle and a variety of measurements that can be derived from images or other instruments. It also presents a study using the k-means algorithm to generate new ways of clustering a batch of cattle using the measurements that most correlate with the animal's body weight and visual scores.
Cite
@article{arxiv.2403.07137,
title = {Exploring Cluster Analysis in Nelore Cattle Visual Score Attribution},
author = {Alexandre de Oliveira Bezerra and Rodrigo Goncalves Mateus and Vanessa Ap. de Moraes Weber and Fabricio de Lima Weber and Yasmin Alves de Arruda and Rodrigo da Costa Gomes and Gabriel Toshio Hirokawa Higa and Hemerson Pistori},
journal= {arXiv preprint arXiv:2403.07137},
year = {2024}
}