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Published in:

Volume 7 Issue 11
November-2020
eISSN: 2349-5162

Unique Identifier

JETIR2011016

Page Number

99-105

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Title

Deep Learning for Plant Species Classification

ISSN

2349-5162

Cite This Article

"Deep Learning for Plant Species Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.99-105, November-2020, Available :http://www.jetir.org/papers/JETIR2011016.pdf

Abstract

Plants are amid the earth's helpful and attractive products of environment. A plant has been vital to mankind's endurance. The urgent require is the more plant was at the risk of extermination. An ayurvedic medicines can be prepared by using the plant leaves and this plant class belong to the endanger group. So it is crucial to set up the database for plant defense. Plant leaf detection has been challenge for several researchers. In this paper, introduced on the survey of various classification methods is used for the plant leaves classification. In this paper CNN is used to classify plant from its leaves. A combination of texture and color features are extracted and then fed to modified CNN classifier. The system was attained an accuracy more than 94.26% with the help of tensorflow framework. The model automatically classifies 17 different plant species.

Key Words

tropical tree, profound learning, Convolutional Network, leaf vein morphometric, highlight extraction, characterization

Cite This Article

"Deep Learning for Plant Species Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp99-105, November-2020, Available at : http://www.jetir.org/papers/JETIR2011016.pdf

Publication Details

Published Paper ID: JETIR2011016
Registration ID: 303170
Published In: Volume 7 | Issue 11 | Year November-2020
DOI (Digital Object Identifier):
Page No: 99-105
ISSN Number: 2349-5162

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Cite This Article

"Deep Learning for Plant Species Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp99-105, November-2020, Available at : http://www.jetir.org/papers/JETIR2011016.pdf




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