Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/348123
Title: Agribus Advanced Growth Metric with Region Based CNN for Identification of Plant Diseases without Bias in an Unbalanced Stream of Data A Predictive Plant Disease Classifier
Researcher: Deeba K
Guide(s): Amutha B
Keywords: Automation and Control Systems
Computer Science
Engineering and Technology
University: SRM University
Completed Date: 2021
Abstract: The developments invited for the thesis - AGRIBUS corresponds to the initial design of framing the objectives for the growth of muskmelon in 1 acre of land. This 1 acre of land has been customized to ascertain the properties of the land along with its soil condition and climatic factors. The diseases relate to the growth of the plant which affect at different conditions have to be forecasted and analyzed properly in advance so that the disease prediction mechanism and the number of days in advance the diseases are being predicted will be a boon for the farmers to gross an action of applying fertilizers, watering properly and applying pesticides in time for the better growth of plants and to acquire the best yield out of it newline
Pagination: 
URI: http://hdl.handle.net/10603/348123
Appears in Departments:Department of Computer Science Engineering

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certificate page.pdf529.95 kBAdobe PDFView/Open
chapter 1.pdf2.29 MBAdobe PDFView/Open
chapter 2.pdf1.45 MBAdobe PDFView/Open
chapter 3.pdf1.35 MBAdobe PDFView/Open
chapter 4.pdf712.62 kBAdobe PDFView/Open
chapter 5.pdf1.53 MBAdobe PDFView/Open
chapter 6.pdf1.52 MBAdobe PDFView/Open
chapter 7.pdf173.85 kBAdobe PDFView/Open
curriculum vitae.pdf20.92 kBAdobe PDFView/Open
list of publications.pdf453.46 kBAdobe PDFView/Open
preliminary page.pdf590.17 kBAdobe PDFView/Open
references.pdf224.04 kBAdobe PDFView/Open
title page.pdf359.27 kBAdobe PDFView/Open
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