UGC Approved Journal no 63975(19)

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

Volume 9 Issue 3
March-2022
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2203468


Registration ID:
321646

Page Number

e532-e536

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Title

Survey On Rice Leaf Disease Detection Using Machine Learning And Deep Learning Techniques

Abstract

Rice is considered as one of the most important crops in India, rice crop is much vulnerable to illness. The disease that presents on plant leaves can be fungal disease, bacterial diseases or any other types of diseases. If farmers fail to identify a disease that on rice crop leaves, then it results in crop failure, it is one of the challenges that farmers confront, and as a result, it has an impact on rice production and makes delivering high-quality and quantity food to the population extremely difficult. It certainly increases the economic crisis in the agricultural field, and increase in price of rice crop. Most of farmers for their living expenses they rely upon agriculture and if it fails, they will face hard time, nowadays farmers commit suicide because of financial losses in agriculture. The manual identification definite disease is time consuming and not efficient, if definite disease is found, then farmers can take all sort of various disease control procedures in earlier stage, can also prevent from crop failure. For rice leaf disease detection, various methods and techniques are used. Bacterial leaf blight, Leaf smut, Hispa, and Brown spot diseased images are considered and segmented using Image processing technique, and important features are extracted from the segmented area using feature extraction method. These features will be used as inputs in neural network or machine learning classification algorithms that are able to detect the exact disease

Key Words

Rice leaf disease detection,Image processing, Feature extraction, Machine learning and Deep learning algorithms.

Cite This Article

"Survey On Rice Leaf Disease Detection Using Machine Learning And Deep Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.e532-e536, March-2022, Available :http://www.jetir.org/papers/JETIR2203468.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

"Survey On Rice Leaf Disease Detection Using Machine Learning And Deep Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppe532-e536, March-2022, Available at : http://www.jetir.org/papers/JETIR2203468.pdf

Publication Details

Published Paper ID: JETIR2203468
Registration ID: 321646
Published In: Volume 9 | Issue 3 | Year March-2022
DOI (Digital Object Identifier):
Page No: e532-e536
Country: , , .
Area: Science
ISSN Number: 2349-5162
Publisher: IJ Publication


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