Lumpy skin disease diagnosis in cattle: A deep learning approach optimized with RMSProp and MobileNetV2
Lumpy skin disease (LSD) is a critical problem for cattle populations, affecting both individual cows and the entire herd. Given cattle’s critical role in meeting human needs, effective management of this disease is essential to prevent significant losses. The study proposes a deep learning approach using the MobileNetV2 model and the RMSprop optimizer to address this challenge. Tests on a dataset of healthy and lumpy cattle images show an impressive accuracy of 95%, outperforming existing benchmarks by 4–10%. These results underline the potential of the proposed methodology to revolutionize the diagnosis and management of skin diseases in cattle farming. Researchers and graduate students are the audience for our paper.
Authors
- Tehseen Mazhar (ORCID: https://orcid.org/0000-0002-4649-2376)
- Mohamed Tahar Ben Othman (ORCID: https://orcid.org/0000-0002-0990-5805)
- Sheikh Muhammad Saqib (ORCID: https://orcid.org/0000-0002-4647-1698)
- Yazeed Yasin Ghadi (ORCID: https://orcid.org/0000-0002-7121-495X)
- Muhammad Iqbal
- Tariq Shahazad
- Sulaiman Alamro
Institutions
- Qassim University (SA)
- COMSATS University Islamabad (PK)
- Al Ain University (AE)
- Gomal University (PK)
- Virtual University of Pakistan (PK)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1371/journal.pone.0302862
- Citations
- 29
- Primary Topic
- Poxvirus research and outbreaks
- Type
- article
- Field-Weighted Citation Impact
- 8.51
Funders
- Qassim University