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Review on Different Types of Leaf Disease Detection Methods

Author

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  • Sheshang Degadwala
  • Dhairya Vyas

Abstract

This review explores the various methods employed in detecting leaf diseases, highlighting their significance in ensuring healthy crop yields. The paper examines traditional techniques like visual inspection and microscopy, as well as advanced methods that leverage machine learning, image processing, and deep learning algorithms. Emphasis is placed on the accuracy, efficiency, and scalability of these approaches, considering the challenges of real-time disease detection in diverse environmental conditions. By comparing the strengths and limitations of different methods, the review aims to provide a comprehensive understanding of the current state and future directions in leaf disease detection technology.

Suggested Citation

  • Sheshang Degadwala & Dhairya Vyas, 2024. "Review on Different Types of Leaf Disease Detection Methods," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(4), pages 289-305, August.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i4:id:284
    DOI: 10.32628/CSEIT24104132
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24104132
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