Utilizing Extreme Learning Machine for the Diagnosis of Lumpy Skin Disease in Cattle
Utilizing Extreme Learning Machine for the Diagnosis of Lumpy Skin Disease in Cattle |
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| © 2024 by IJETT Journal | ||
| Volume-72 Issue-9 |
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| Year of Publication : 2024 | ||
| Author : Goddeti Mallikarjun, V.A. Narayana |
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| DOI : 10.14445/22315381/IJETT-V72I9P106 | ||
How to Cite?
Goddeti Mallikarjun, V.A. Narayana, "Utilizing Extreme Learning Machine for the Diagnosis of Lumpy Skin Disease in Cattle," International Journal of Engineering Trends and Technology, vol. 72, no. 9, pp. 67-77, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I9P106
Abstract
Lumpy Skin Disease poses a remarkable threat to livestock, underscoring the urgent necessity for accurate diagnostic methodologies to enable timely intervention. The profound economic ramifications of LSD further underscore the importance of efficient diagnosis. In this context, Artificial Intelligence (AI) emerges as a transformative solution, pivotal in providing swift detection capabilities. Rapid identification of LSD not only mitigates economic burdens but also hinders the disease's spread within herds. A pioneering approach involves the utilization of Extreme Learning Machines (ELM) in tandem with VGG16 for feature extraction, tailored explicitly for LSD diagnosis. This strategy is adept at discerning intricate patterns in disease manifestation, achieving a good accuracy rate of 96.5%. The model's effectiveness is evident in its ability to differentiate between infected and healthy cases with high precision, recall, and F1 score metrics, highlighting its reliability as a dependable tool for accurate LSD diagnosis and intervention. This advancement significantly contributes to the overall health and economic stability of livestock populations, offering a promising avenue for combating the challenges posed by LSD outbreaks.
Keywords
Lumpy Skin Disease, Extreme Learning Machine, Convolutional Neural Network, VGG16, Hyperparameter.
References
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