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Rice Leaf Disease Classification Using CNN

EasyChair Preprint no. 11245

12 pagesDate: November 5, 2023


Rice is amongst the majorly cultivated crops in India and its leaf diseases can

have a substantial impact on output and quality. The most important component is identifying rice leaf

diseases, which have a direct impact on the economy and food security. Brown spot, Leaf Blast, Hispa

are the most frequently occurring rice leaf diseases. To resolve this issue, we have studied various

machine learning and deep learning approaches for detecting the diseases on their leaves by calculating

their accuracy, recall, and precision to measure the performance. This study helps the farmers by

detecting the diseases in rice leaves in order to get a healthy crop yield. The deep learning models

perform well when compared with the machine learning methods.

Keyphrases: Convolutional Neural Networks, deep learning, machine learning, Rice leaf diseases, Transfer Learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Adhikari Durga Venkata Madhav and Amanchi Sravan Kumar and Addanki Gargeya and Allam Rohit Sree Ranga and S Sujitha},
  title = {Rice Leaf Disease Classification Using CNN},
  howpublished = {EasyChair Preprint no. 11245},

  year = {EasyChair, 2023}}
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