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A Novel Optimized Convolutional Neural Network Based on Marine Predators Algorithm for Citrus Fruit Quality Classification

In: Liss 2021

Author

Listed:
  • Gehad Ismail Sayed

    (Faculty of Computers and AI and Scientific Research Group in Egypt (SRGE))

  • Aboul Ella Hassanien

    (Faculty of Computers and AI and Scientific Research Group in Egypt (SRGE))

  • Mincong Tang

    (Beijing Jiaotong University)

Abstract

Plant diseases have a huge impact on the reduction in production in agriculture. This may lead to economic losses. Citrus is one of the major sources of nutrients on the planet such as vitamin C. Last decade, machine learning algorithms have been widely used for the classification of diseases in plants. In this paper, a new hybrid approach based on the marine predators algorithm (MPA) and convolutional neural network for the classification of citrus disease is proposed. MPA is used to find the optimal values of batch size, drop-out rate, drop-out period, and maximum epochs. The experimental results showed that the proposed optimized ResNet50 based on MPA is superior. It achieved overall accuracy 100% for citrus disease classification.

Suggested Citation

  • Gehad Ismail Sayed & Aboul Ella Hassanien & Mincong Tang, 2022. "A Novel Optimized Convolutional Neural Network Based on Marine Predators Algorithm for Citrus Fruit Quality Classification," Lecture Notes in Operations Research, in: Xianliang Shi & Gábor Bohács & Yixuan Ma & Daqing Gong & Xiaopu Shang (ed.), Liss 2021, pages 682-692, Springer.
    • Handle: RePEc:spr:lnopch:978-981-16-8656-6_60
    DOI: 10.1007/978-981-16-8656-6_60
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