Paper Contents
Abstract
Lumpy Skin Disease (LSD) is a highly contagious viral infection that significantly impacts cattle and poses a threat to the global livestock industry. Traditional diagnostic methods are often slow and prone to inaccuracies, which delay timely interventions and exacerbate the spread of the disease. This research introduces a novel machine-learning-based diagnostic system leveraging Convolutional Neural Networks (CNNs) and MobileNet architectures to detect LSD efficiently and accurately. The system utilizes image-based analysis of cattle skin to classify them as either affected or healthy, reducing reliance on subjective or time-consuming laboratory tests. This innovative approach offers a scalable and effective solution for veterinary practices and livestock management, helping to mitigate economic losses and enhance animal health outcomes.
Copyright
Copyright © 2025 Rakshitha S. This is an open access article distributed under the Creative Commons Attribution License.
