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Reseach Article

A Novel Approach for Plant Identification

by Sonali A. Kanade, Chaitali S. Patil, Tejaswini S. Pawar, Ashok R. Ambore, Hemant D. Sonawavne
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 5
Year of Publication: 2017
Authors: Sonali A. Kanade, Chaitali S. Patil, Tejaswini S. Pawar, Ashok R. Ambore, Hemant D. Sonawavne
10.5120/ijca2017915752

Sonali A. Kanade, Chaitali S. Patil, Tejaswini S. Pawar, Ashok R. Ambore, Hemant D. Sonawavne . A Novel Approach for Plant Identification. International Journal of Computer Applications. 177, 5 ( Nov 2017), 7-9. DOI=10.5120/ijca2017915752

@article{ 10.5120/ijca2017915752,
author = { Sonali A. Kanade, Chaitali S. Patil, Tejaswini S. Pawar, Ashok R. Ambore, Hemant D. Sonawavne },
title = { A Novel Approach for Plant Identification },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2017 },
volume = { 177 },
number = { 5 },
month = { Nov },
year = { 2017 },
issn = { 0975-8887 },
pages = { 7-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number5/28620-2017915752/ },
doi = { 10.5120/ijca2017915752 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:45:01.314205+05:30
%A Sonali A. Kanade
%A Chaitali S. Patil
%A Tejaswini S. Pawar
%A Ashok R. Ambore
%A Hemant D. Sonawavne
%T A Novel Approach for Plant Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 5
%P 7-9
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Plant Identification has a place with a particular application space of data mining. Pictures of plant leaves are generally utilized as the primary component to recognize a plant from another. For legitimate recognizable proof, highlight extraction is essential. In the literature, most plant acknowledgment frameworks utilize the highlights alongside a grouping technique, which has been adjusted or changed to confront this kind of application. In this paper, we are building up a portable application for distinguishing restorative plants which utilizes Profound Learning and Convolutional Neural System to take in discriminative highlights from leaf pictures with classifiers for plant ID. We propose three new geometric highlights that depict the vertical and level symmetry of clears out. These highlights are easy to separate from pictures. As per the consequences of trials, when these highlights are utilized as a part of conjunction with other surely understood geometric attributes, the execution of traditional order strategies is amazingly moved forward. To demonstrate the adequacy of the proposition, We test few classifiers with pictures of leaves openly accessible on We, This framework will manage professionals of Ayurveda and ordinary android clients too.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Identification Dataset Feature Extraction Plant Recognition geometric feature