plant and fruit diagnosis and treatment through deep learning

Registration ID: IJNRD_194999

Published ID: IJNRD2305290

DOI: Click Here to Get

Ram paul , Sachin kumar , Mayank khandelwal , Ishu khandelwal , Tushar goyal

machine learning, ML, Plant health, Deep learning

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.

Published Paper   E-Certificate

Ram paul, Sachin kumar, Mayank khandelwal, Ishu khandelwal, & Tushar goyal (May-2023). plant and fruit diagnosis and treatment through deep learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), c707-c711. https://ijnrd.org/papers/IJNRD2305290.pdf

Volume 8 Issue 5, May-2023

Pages : c707-c711

Paper Reg. ID: IJNRD_194999

Published Paper Id: IJNRD2305290

Downloads: 000121982

Research Area: Computer Science & Technology 

Country: noida, Uttar Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305290.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305290

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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