Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning

Advances in neural networks have garnered growing interest in applications of machine vision in livestock management, but simpler landmark-based approaches suitable for small, early stage exploratory studies still represent a critical stepping stone towards these more sophisticated analyses. While s...

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Detalles Bibliográficos
Autores principales: McVey, Catherine, Egger, Daniel, Pinedo, Pablo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653925/
https://www.ncbi.nlm.nih.gov/pubmed/36366045
http://dx.doi.org/10.3390/s22218347

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653925/
https://www.ncbi.nlm.nih.gov/pubmed/36366045
http://dx.doi.org/10.3390/s22218347

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