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)
Analysing plant phenotype stands as a
pivotal component in understanding plant
development. This study introduces a streamlined
methodology aimed at discerning between healthy
and diseased or infected leaves through the
integration of image processing and machine learning
methodologies. Diverse ailments impair leaf
chlorophyll, manifesting as discoloured spots on the
leaf surface, typically brown or black in hue. The
proposed approach employs a sequence of
techniques including image preprocessing,
segmentation, feature extraction, and machine
learning-based classification. Notably, the
incorporation of a convolutional neural network
(CNN) notably enhances detection accuracy.
"Potato Leaf disease detection using Deep learning ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.d90-d92, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404312.pdf
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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
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