UGC Approved Journal no 63975(19)

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

Volume 8 Issue 12
December-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2112391


Registration ID:
318208

Page Number

d781-d787

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Title

DISEASES RECOGNITION FOR ORYZA SATIVA LEAF PLANT BASED ON ARTIFICIAL AND CONVOLUTIONAL NEURAL NETWORK

Abstract

Plant disease is one of the major problems in the agriculture sector. Plants are affected by a various factor such as bacteria, fungi, viruses etc.In this Project, we propose a structure to detect a paddy leaf disease more accurately. The proposed system consists of artificial and convolutional neural network (feed-forward artificial neural network) for plant disease classification. The different types of classifier is analysed. ANN consists of machine learning algorithm and it is trained by choosing feature value that may well classify four type of diseased samples appropriately. CNN architecture includes the three hidden layer(convolution, pooling, fully connected layer) and it used to classify more accurately. As a result, few diseases that usually occurs in paddy plants such as bacterial blight, brown spot, leaf blast and leaf streak are detected.CNN model achieves more accuracy for identifying the leaf disease in the paddy plant thereby showing the feasibility of its usage in real time application

Key Words

Deep learning, CNN, Paddy plant

Cite This Article

"DISEASES RECOGNITION FOR ORYZA SATIVA LEAF PLANT BASED ON ARTIFICIAL AND CONVOLUTIONAL NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.d781-d787, December-2021, Available :http://www.jetir.org/papers/JETIR2112391.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

"DISEASES RECOGNITION FOR ORYZA SATIVA LEAF PLANT BASED ON ARTIFICIAL AND CONVOLUTIONAL NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppd781-d787, December-2021, Available at : http://www.jetir.org/papers/JETIR2112391.pdf

Publication Details

Published Paper ID: JETIR2112391
Registration ID: 318208
Published In: Volume 8 | Issue 12 | Year December-2021
DOI (Digital Object Identifier):
Page No: d781-d787
Country: ARIYALUR, TAMIL NADU, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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