Sugarcane leaf disease classification using deep neural network approach.

Journal: BMC plant biology
PMID: 40033192

Abstract

OBJECTIVE: The objective is to develop a reliable deep learning (DL) based model that can accurately diagnose diseases. It seeks to address the challenges posed by the traditional approach of manually diagnosing diseases to enhance the control of disease and sugarcane production.

Authors

  • Saravanan Srinivasan
    Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, India.
  • S M Prabin
    School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, India.
  • Sandeep Kumar Mathivanan
    School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India.
  • Hariharan Rajadurai
    School of Computing Science and Engineering, VIT Bhopal University, Bhopal-Indore Highway Kothrikalan, Sehore, MP, India.
  • Suresh Kulandaivelu
    School of Computer Science and Engineering, Galgotias University, Greater Noida, 203201, India.
  • Mohd Asif Shah
    Bakhtar University, Kabul, Afghanistan.

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