Lumpy skin disease diagnosis in cattle: A deep learning approach optimized with RMSProp and MobileNetV2.

Journal: PloS one
PMID: 39102387

Abstract

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

  • Sheikh Muhammad Saqib
    Institute of Computing and Information Technology, Gomal University, Dera Ismail Khan, Pakistan.
  • Muhammad Iqbal
    Department of Computer Science, Abdul Wali Khan University Mardan, Pakistan.
  • Mohamed Tahar Ben Othman
    Department of Computer Science, College of Computer, Qassim University, Buraydah, Saudi Arabia.
  • Tariq Shahazad
    Department of Computer Science, COMSATS University Islamabad, Sahiwal, Pakistan.
  • Yazeed Yasin Ghadi
    Department of Computer Science and Software Engineering, Al Ain University, Abu Dhabi, United Arab Emirates.
  • Sulaiman Al-Amro
    Department of Computer Science, College of Computer, Qassim University, Buraydah, Saudi Arabia.
  • Tehseen Mazhar
    Department of Computer Science, Virtual University of Pakistan, Lahore, Punjab, Pakistan.

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