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dc.contributor.authorIslam, Sabrina
dc.contributor.authorPaul, Apurba
dc.contributor.authorChowdhury, Oishe Roy
dc.contributor.authorFiza, Fahmida Akhter
dc.date.accessioned2024-04-28T05:30:40Z
dc.date.available2024-04-28T05:30:40Z
dc.date.copyright©2023
dc.date.issued2023-12
dc.identifier.otherID: 20121011
dc.identifier.otherID: 20121033
dc.identifier.otherID: 19121130
dc.identifier.otherID: 20121007
dc.identifier.urihttp://hdl.handle.net/10361/22682
dc.descriptionThis final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2023.en_US
dc.descriptionCataloged from PDF version of final year design project.
dc.descriptionIncludes bibliographical references (pages 82-84).
dc.description.abstractThis work aims to design and implement a disease detection system for mango leaves. We have proposed two design approaches for the disease detection system for mango leaves. From these two design approaches, we have performed simulation and analysis to get the best design approach. The best design approach includes a pest disease detection system with a rover body. We have trained our model to detect 9 types of pest diseases in mango leaves with the help of available datasets. We have performed the test of the pest disease detection system with the rover body in a particular field. In that field, we have got 3 diseases that were detected by our rover body system successfully. Our pest disease detection system can easily expand up to the required height for the particular testing field and can detect successfully the pest diseases of the mango leaves which completes our entire project.en_US
dc.description.statementofresponsibilitySabrina Islam
dc.description.statementofresponsibilityApurba Paul
dc.description.statementofresponsibilityOishe Roy Chowdhury
dc.description.statementofresponsibilityFahmida Akhter Fiza
dc.format.extent127 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University project reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectAgricultural roboticsen_US
dc.subjectImage processingen_US
dc.subjectDisease detectionen_US
dc.subjectMango leaves pesten_US
dc.subject.lcshArtificial intelligence--Agricultural applications.
dc.subject.lcshPlant diseases.
dc.titleDisease detection system of mango leavesen_US
dc.typeProject reporten_US
dc.contributor.departmentDepartment of Electrical and Electronic Engineering, Brac University
dc.description.degreeB. Electrical and Electronic Engineering


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