IJNRD Research Journal

WhatsApp
Click Here

WhatsApp editor@ijnrd.org
IJNRD
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.76

Issue per Year : 12

Volume Published : 8

Issue Published : 80

Article Submitted : 7144

Article Published : 2923

Total Authors : 7078

Total Reviewer : 714

Total Countries : 89

Indexing Partner

Join RMS/Earn 300

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Plant Disease Identification Using Supervised Learning
Authors Name: Nishana N , Nowfia N , Subina Thajudeen , Sumi Sunil , Sithara
Download E-Certificate: Download
Author Reg. ID:
IJNRD_181408
Published Paper Id: IJNRD2205080
Published In: Volume 7 Issue 5, May-2022
DOI:
Abstract: In recent years, a server-based and mobile-based approach to disease identification has been used. Detecting disease signals quickly and accurately is a critical difficulty in crop protection. Pests and Diseases results in a destruction of crops or part of the plant resulting in decreased food productions leading to food insecurity. Visual identification of diseases in a large farm by experts and agronomists is the primary approach in developing countries which is time-consuming and costly. The proposed system is a mobile application for farmers It also provide disease detection, provide seeds and pesticide name can be prescribe to farmer. Overall, using machine learning to train the large datasets available publicly gives as a clear way to detect the disease present in plants.
Keywords: Convolutional Neural Network (CNN), Deep Learning, Supervised Learning
Cite Article: "Plant Disease Identification Using Supervised Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 5, page no.732-736, May-2022, Available :http://www.ijnrd.org/papers/IJNRD2205080.pdf
Downloads: 000111350
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID:IJNRD2205080
Registration ID: 181408
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 732-736
Country: -, -, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2205080
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2205080
Share Article:
Share

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijnrd.org
Semantic Scholar Microsaoft Academic ORCID Zenodo
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX PUBLON
DRJI SSRN Scribd DocStoc

ISSN Details

ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to Get DOI? DOI

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Join RMS/Earn 300

IJNRD