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)
It is critical to have control over plant disease since it influences the overall quality and number of species of the plants, plus the nation's infrastructure. To avoid revenue damage and the endangerment of particular species, automated detection and sorting of leaf illness is critical. In past, numerous machine learning (ML) models have been suggested to observe and treat plant disease; nevertheless, they are not accessible because of the difficulty of procuring advanced equipment, the restricted scalability of models, and the complexity and inefficiencies of their application. Local expertise and previous experiences have historically been used to diagnose plant pathogens. A plant's health may be determined by a qualified specialist. If an unhealthy plant is discovered, signs appear on its leaves and fruits. Diagnosis of plant disease is hard because of the fact that leaves have distinct symptoms that need to be examined. Even experienced plant pathologists and agronomists have trouble differentiating among various illnesses because of the quantity of adult plants, their extensive prior phytostatic problems, and their inherent ambiguity. This research paper will undergo ML/ deep learning in the field of plant health analysis.
Keywords:
machine learning, ML, Plant health, Deep learning
Cite Article:
"plant and fruit diagnosis and treatment through deep learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.c707-c711, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305290.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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