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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM36648

Harnessing Machine Learning for Flora Disease Detection: A Survey of App-Based Approach

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM36648

Volume:

8 |

7 |

Jul 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM36648

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

SD

Supriyaa. D

RPC

Riya Princy. C

PPS

Poorna Pushkala. S

RM

Ramya. M

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Abstract

This project aims to develop an AI-based plant disease detection app, leveraging various AI techniques such as machine learning and deep learning models. The primary focus lies in accurately identifying and segmenting diseased plant areas from healthy ones. For precise lesion segmentation, the app utilizes artificial intelligence methods like convolutional neural networks (CNNs) and image processing algorithms. By integrating segmentation and classification techniques, the app offers a comprehensive analysis of plant diseases based on visual symptoms such as discoloration, texture irregularities, and patterns. Users can categorize different plant diseases, receive recommendations for treatments or preventive measures, and conveniently purchase recommended products through the app.

KEYWORDS

Plant disease disease detection preventive measures recommendation.

Cite This Article

Supriyaa. D, Riya Princy. C, Poorna Pushkala. S, Ramya. M, "Harnessing Machine Learning for Flora Disease Detection: A Survey of App-Based Approach," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 7, Jul 2024. https://doi.org/10.55041/IJSREM36648

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Publication Date

7/20/2024

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Double-Blind Peer Review

Review Rounds: 2

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