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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM36460

AI BASED ARECANUT PLANT DISEASE CLASSIFICATION SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM36460

Volume:

8 |

7 |

Jul 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM36460

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

LMU

Likhitha M U

DGM

Dr. Geetha M

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Abstract

Arecanut, commonly known as betel nut, is a vital cash crop in many tropical regions, contributing significantly to the agricultural economy. However, like other crops, arecanut plants are susceptible to various diseases that can severely impact yield and quality. Early detection and accurate classification of these diseases are crucial for timely intervention and effective disease management. In this study, we propose an AI-based arecanut plant disease classification system that leverages deep learning techniques to automatically identify and classify different diseases affecting arecanut plants. Convolutional neural networks (CNNs) are employed for feature extraction and disease classification, with transfer learning techniques used to fine-tune pre-trained models on the specific task of arecanut disease recognition.

KEYWORDS

Arecanut betel nut plant disease classification deep learning transfer learning agricultural AI disease management

Cite This Article

Likhitha M U, Dr. Geetha M, "AI BASED ARECANUT PLANT DISEASE CLASSIFICATION SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024. https://doi.org/10.55041/IJSREM36460

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Publication Date

7/15/2024

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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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