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 : 9

Issue Published : 96

Article Submitted :

Article Published :

Total Authors :

Total Reviewer :

Total Countries :

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: Classification Of Rice Leaf Diseases Using Transfer Learning With CNN
Authors Name: M Madhav Reddy , N Sripriya , P Pavan Kalyan , Y Charan
Download E-Certificate: Download
Author Reg. ID:
IJNRD_195242
Published Paper Id: IJNRD2305371
Published In: Volume 8 Issue 5, May-2023
DOI:
Abstract: One of the most widely grown crops in India is rice, which is afflicted by a number of illnesses at different phases of its development. With their limited understanding, farmers find it extremely challenging to manually detect these diseases effectively. Recent advancements in deep learning demonstrate how Convolutional Neural Network (CN N) model-based automatic image recognition systems can be quite helpful in solving such issues. Since there aren't many image datasets available for the rice leaf disease, we developed our own, small dataset and utilised Transfer Learning to build our deep learning model. The dataset gathered from rice fields and the internet was used to train and test the suggested CNN architecture, which is based on VGG16.
Keywords: Convolutional Neural Network, Deep Learning, Fine-Tuning, Rice Leaf Diseases, Transfer Learning
Cite Article: " Classification Of Rice Leaf Diseases Using Transfer Learning With CNN", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.d559-d563, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305371.pdf
Downloads: 000118753
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:IJNRD2305371
Registration ID: 195242
Published In: Volume 8 Issue 5, May-2023
DOI (Digital Object Identifier):
Page No: d559-d563
Country: thiruvallur, tamil nadu, India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305371
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305371
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