Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8279
Title: Plant Disease Detection
Authors: Kanwar, Sanya
Gupta, Stuti
Verma, Ruchi [Guided by]
Keywords: Plant disease detection
Manual plant disease identification
Issue Date: 2022
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Plant disease detection is crucial in agriculture, as farmers must frequently make decisions such as whether or not the crop is sufficient. These can produce major system difficulties that impair each product's quality, quantity, or productivity, and they should be treated carefully. Plant diseases produce frequent disease outbreaks, result in large numbers of deaths, and have significant economic implications. These issues must be addressed quickly in order to save lives and money. Plant disease categorization by machine is a hot research issue. Because it is critical to be able to recognize the disease symptoms that occur on the plant's leaves when monitoringAa vast region and at an early stage. This enables image-based automated inspection usingAcomputer vision techniques. Manual plant disease identification, on the other hand, is aAtime-consuming, incorrect operationAthat can only be done in a small area at a time. PlantAillnesses can be detected early this way, and pestAand infection management techniques can be utilized to solve pest problems while reducing hazards to humans and theAenvironment, or so they believed. We describe the current trends and difficulties of plant leaf diseases using extensive research and modern imaging techniques. We hope that, for all intents and purposes, thisAresearch will be of enormous use to researchers studyingAplant and insect illnesses, or so they thought. Also, we talked about some of the most pressing concerns and issues that needed to beAhandled, or so they believed.
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8279
Appears in Collections:B.Tech. Project Reports

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