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Artificial Intelligence on Farms: Sheep Breed Classification Using Computer Vision

Indian Agricultural Research Journals

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Title Artificial Intelligence on Farms: Sheep Breed Classification Using Computer Vision
 
Creator Hamadani, Ambreen
 
Description As the challenges of population explosion, food security and climate change become more pressing, there is a dire need to produce more food. Since animal husbandry is a crucial part of agriculture, production per farm has to also increase substantially over the next few years. This is especially important for developing countries where the introduction of technology and automation can remove drudgery, improve efficiency and reduce labour. An important part of this is the use of images for automatic animal monitoring. This research was therefore undertaken to classify four breeds using three artificial intelligence algorithms; K-nearest neighbours, Support Vector Machines and Convolutional Neural Networks (CNNs) which were evaluated and ranked. We thus developed three deployable models for image classification among which pre-trained CNNs had the highest accuracy of 0.90. We conclude that image classification therefore is useful for automatic animal classification and monitoring. This would help improve the production potential of farms through the automation of farm tasks.
 
Publisher The Indian Society of Animal Production and Management
 
Date 2024-10-02
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://epubs.icar.org.in/index.php/IJAPM/article/view/154432
10.48165/ijapm.2024.40.4.8
 
Source Indian Journal of Animal Production and Management; Vol. 40 No. 4 (2024): Indian Journal of Animal Production and Management; 260-268
2350-0182
0970-1524
 
Language eng
 
Relation https://epubs.icar.org.in/index.php/IJAPM/article/view/154432/56086
 
Rights Copyright (c) 2024 The Publisher
https://creativecommons.org/licenses/by-nc/4.0