UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRFX06030


Registration ID:
517001

Page Number

184-189

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Title

Plant Leaf Disease Detection – A Machine Learning Approach

Abstract

Agriculture proves to be major source of income for many farmers in our country. According to survey conducted in 2021 58% of population depends on agriculture. Besides, many farmers are cultivating in remote areas of the world with the lack of accurate knowledge and disease detection, however, they rely on manual observation on grains and vegetables, as a result, they are suffering from a great loss. For overcoming such issues there is need to demonstrate a practice where farmers can easily detect plant leaf diseases in early stages. Since, for addressing such issues digital farming practices can be involved where use of machine learning algorithm can be used. Eventually, along with detected disease remedy can also be insisted.

Key Words

Agriculture, Vegetables, Farmers, Disease, Detection, Machine Learning.

Cite This Article

"Plant Leaf Disease Detection – A Machine Learning Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.184-189, May-2023, Available :http://www.jetir.org/papers/JETIRFX06030.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Plant Leaf Disease Detection – A Machine Learning Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp184-189, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06030.pdf

Publication Details

Published Paper ID: JETIRFX06030
Registration ID: 517001
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: 184-189
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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