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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM29103

Review on Detection and Prediction of Diseases in Arecanut Trees

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM29103

Volume:

8 |

3 |

Mar 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM29103

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PRN

Pushpa R N

BGB

Bhoomika G B

SG

Shreya G

VHB

Vachana H Belgod

VMS

Vinayashree M Shet

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Abstract

In this study, we propose a method for detecting and predicting diseases in arecanut plants using image processing. The proposed method consists of three main steps: image acquisition, image segmentation, and disease detection and prediction. The performance of the proposed method is evaluated using a dataset of arecanut leaf images with various diseases. The results show that the proposed method can accurately detect and predict the presence of diseases in the arecanut plants with high precision and recall rates.

KEYWORDS

Arecanut Machine learning Convolutional neural networks.

Cite This Article

Pushpa R N, Bhoomika G B, Shreya G, Vachana H Belgod, Vinayashree M Shet, "Review on Detection and Prediction of Diseases in Arecanut Trees," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 3, Mar 2024. https://doi.org/10.55041/IJSREM29103

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Publication Date

12/31/45357

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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