An approach-based machine learning and automated thermal images to predict the dark-cutting incidence in cattle management of healthcare supply chain-Reference-Cited by-同舟云学术

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An approach-based machine learning and automated thermal images to predict the dark-cutting incidence in cattle management of healthcare supply chain

Published:2024-09 Issue: Volume:135 Page:108804
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Jaddoa Mohammed Ahmed^ORCID,Zaidan Aws Alaa,Gonzalez Luciano Adrian,Deveci Muhammet,Cuthbertson Holly,Al-Jumaily Adel,Kadry Seifedine

Funder

Meat and Livestock Australia

Australian Meat Processor Corporation

University of Sydney

Publisher

Elsevier BV

Reference40 articles.

1. Comparative approaches to the investigation of responses to stress and viral infection in cattle;Aich;OMICS A J. Integr. Biol.,2007

2. Forecasting sustainability of healthcare supply chains using deep learning and network data envelopment analysis;Azadi;J. Bus. Res.,2023

3. Predicting dairy cattle heat stress using machine learning techniques;Becker;J. Dairy Sci.,2021

4. Update of Meat Standards Australia and the cuts based grading scheme for beef and sheepmeat;Bonny;J. Integr. Agric.,2018

5. Animal Welfare Science: History and Concepts;Broom,2014

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