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    ARTICLE

    Rice Leaves Disease Diagnose Empowered with Transfer Learning

    Nouh Sabri Elmitwally1,2, Maria Tariq3,4, Muhammad Adnan Khan5,*, Munir Ahmad3, Sagheer Abbas3, Fahad Mazaed Alotaibi6

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1001-1014, 2022, DOI:10.32604/csse.2022.022017

    Abstract In the agricultural industry, rice infections have resulted in significant productivity and economic losses. The infections must be recognized early on to regulate and mitigate the effects of the attacks. Early diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses, reduce pesticide use, and boost ta country’s economy. Assessing the health of a rice plant through its leaves is usually done as a manual ocular exercise. In this manuscript, three rice plant diseases: Bacterial leaf blight, Brown spot, and Leaf smut, were identified using the Alexnet Model. Our research shows that any reduction in… More >

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