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    Image-Based Automatic Diagnostic System for Tomato Plants Using Deep Learning

    Shaheen Khatoon1,*, Md Maruf Hasan1, Amna Asif1, Majed Alshmari1, Yun-Kiam Yap2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 595-612, 2021, DOI:10.32604/cmc.2021.014580

    Abstract Tomato production is affected by various threats, including pests, pathogens, and nutritional deficiencies during its growth process. If control is not timely, these threats affect the plant-growth, fruit-yield, or even loss of the entire crop, which is a key danger to farmers’ livelihood and food security. Traditional plant disease diagnosis methods heavily rely on plant pathologists that incur high processing time and huge cost. Rapid and cost-effective methods are essential for timely detection and early intervention of basic food threats to ensure food security and reduce substantial economic loss. Recent developments in Artificial Intelligence (AI)… More >

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