IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v10y2025i11p954-962.html

Deep Learning-Based Wheat Disease Detection and Classification System Using Convolutional Neural Networks

Author

Listed:
  • Ms. Drashti Shah

    (B. Tech Computer Engineering, Birla Vishvakarma Mahavidyalaya (BVM) Engineering College, V. V. Nagar)

  • Mr. Dhruv Chauhan

    (B. Tech Computer Engineering, Birla Vishvakarma Mahavidyalaya (BVM) Engineering College, V. V. Nagar)

  • Dr Mahasweta Joshi

    (Assistant Professor, Computer Department, Birla Vishvakarma Mahavidyalaya (BVM) Engineering College, V. V. Nagar)

Abstract

Wheat, one of the major crops in the world, is vulnerable to many diseases that cause tremendous yield and quality loss. This paper proposes a deep learning method for the automatic detection and classification of wheat diseases based on a Convolutional Neural Network (CNN). We respond to the imperative of early and precise identification of diseases in wheat crops in order to reduce agricultural losses.The system learned on a data set of more than 14,000 wheat leaf images corresponding to 15 classes of various rusts, blights, insects, and normal leaves. Our suggested CNN model reached a training accuracy of 97.02% and validation accuracy of 91.00%. The model design uses data augmentation strategies and dropout regularization to promote generalization as well as avoid overfitting

Suggested Citation

  • Ms. Drashti Shah & Mr. Dhruv Chauhan & Dr Mahasweta Joshi, 2025. "Deep Learning-Based Wheat Disease Detection and Classification System Using Convolutional Neural Networks," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(11), pages 954-962, November.
    • Handle: RePEc:bjf:journl:v:10:y:2025:i:11:p:954-962
    as

    Download full text from publisher

    File URL: https://rsisinternational.org/journals/ijrias/uploads/vol10-iss11-pg954-962-202512_pdf.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrias/view/deep-learning-based-wheat-disease-detection-and-classification-system-using-convolutional-neural-networks/
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:journl:v:10:y:2025:i:11:p:954-962. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.