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  • Open Access

    ARTICLE

    EfficientNet-Based Robust Recognition of Peach Plant Diseases in Field Images

    Haleem Farman1, Jamil Ahmad1,*, Bilal Jan2, Yasir Shahzad3, Muhammad Abdullah1, Atta Ullah4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2073-2089, 2022, DOI:10.32604/cmc.2022.018961

    Abstract Plant diseases are a major cause of degraded fruit quality and yield losses. These losses can be significantly reduced with early detection of diseases to ensure their timely treatment, particularly in developing countries. In this regard, an expert system based on deep learning model where the expert knowledge, particularly the one acquired by plant pathologist, is recursively learned by the system and is applied using a smart phone application for use in the target field environment, is being proposed. In this paper, a robust disease detection method is developed based on convolutional neural network (CNN), where its powerful features extraction… More >

  • Open Access

    ARTICLE

    PeachNet: Peach Diseases Detection for Automatic Harvesting

    Wael Alosaimi1,*, Hashem Alyami2, M. Irfan Uddin3

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1665-1677, 2021, DOI:10.32604/cmc.2021.014950

    Abstract To meet the food requirements of the seven billion people on Earth, multiple advancements in agriculture and industry have been made. The main threat to food items is from diseases and pests which affect the quality and quantity of food. Different scientific mechanisms have been developed to protect plants and fruits from pests and diseases and to increase the quantity and quality of food. Still these mechanisms require manual efforts and human expertise to diagnose diseases. In the current decade Artificial Intelligence is used to automate different processes, including agricultural processes, such as automatic harvesting. Machine Learning techniques are becoming… More >

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