Implementation of Disease Detection in Fruits using Neural Networks

Authors

  • G Harish Assistant Professor, Department of Electronics and Communication Engineering, Vignan’s Lara Institute of Technology and Science Guntur, India. Author
  • M Vamsi Krishna Department of Electronics and Communication Engineering, Vignan’s Lara Institute of Technology and Science Guntur, India Author
  • N Sneha Department of Electronics and Communication Engineering, Vignan’s Lara Institute of Technology and Science Guntur, India. Author
  • K Harsha Vardhan Rao Department of Electronics and Communication Engineering, Vignan’s Lara Institute of Technology and Science Guntur, India. Author
  • K Sai Mounika Department of Electronics and Communication Engineering, Vignan’s Lara Institute of Technology and Science Guntur, India. Author

DOI:

https://doi.org/10.47392/irjash.2023.S008

Keywords:

CNN, Preprocessing, Segmentation, Feature extraction, Classifiers

Abstract

Commercialized agricultural operations are always looking for ways to reduce
labour requirements without compromising output. Images of a few different fruit diseases, including Bitter Rot, and Sooty Blotch are employed in this
method. Fruit infections’ ability to lower productivity and the global economy
in the agricultural sector is a frustrating situation. In actuality, a healthy diet
should be built around fruits. India has a population that is approximately 68
per cent dependent on agriculture. A significant percentage of the Indian economy is based on agriculture. Fruit cultivation has been a vital part of agriculture all over the world and has been the foundation of rural economies. Monitoring a plant’s health and spotting illness manually is challenging. Agribusiness is a major contributor to the global economy, but its growth is slowing
when compared to the rise in interest, and this ratio of interest to creation is
expected to maintain high in the next few generations.

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Published

2023-05-01