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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 5, MAY 2022

PLANT HEALTH IDENTIFICATION USING LEAF IMAGES

VANSH ARORA

DOI: 10.17148/IJARCCE.2022.115116

Abstract: Identification of plant health is the new challenging area for the researchers. One of the most important steps in automatic identification of plant diseases is to extract the infected region from the normal portion of the plant. Studying the infected leaves it has been observed that the greenness of the infected portion of the leaves changes significantly with respect to the normal leaves. Images of potato leaves of both categories healthy and diseased captured with digital camera and resolution of 256x256 pixels forms the dataset. CNN model is used for identifying the health status of plants.

Keywords: Convolutional Neural Networks, Plant Health Identification.

How to Cite:

[1] VANSH ARORA, “PLANT HEALTH IDENTIFICATION USING LEAF IMAGES,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.115116