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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Plant Disease Recognition From Leaf Images using CNN
Authors
Shital Kokate, Naganath Bagal, Ganesh Wayal
Keywords
Plant disease, CNN (Convolutional Neural Network), VGG16, Resnet34, Flask
Abstract
Abstract -- Determining the crucial aspects that impact crop
output or plant development is made possible by the
identification of plant diseases, making this a significant
area of research. According to recent studies, 14.1% of
plants perish from plant disease. It's a significant issue that
could affect people's health as well. The greatest number of
plants can be utilised to create medications. This implies
that it's critical to identify plant illnesses early on. This
publication offers a helpful method for identifying illnesses
in various plant species. Other from tomatoes. A wide range
of plant species, including sugarcane, potatoes, apples, grapes, and maize, are recognised and detectable by the
system. With camera-captured images serving as the basis, plant disease detection and treatment are now possible
because to deep learning's recent advancements in computer
vision.
IJCRT's Publication Details
Unique Identification Number - IJCRT2406118
Paper ID - 263159
Page Number(s) - b81-b87
Pubished in - Volume 12 | Issue 6 | June 2024
DOI (Digital Object Identifier) -
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Shital Kokate, Naganath Bagal, Ganesh Wayal, "Plant Disease Recognition From Leaf Images using CNN", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 6, pp.b81-b87, June 2024, Available at :http://www.ijcrt.org/papers/IJCRT2406118.pdf
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Volume 14 | Issue 5
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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