Detección de antracnosis foliar en plantas de mango por medio de análisis de imágenes hiperespectrales

dc.contributor.advisorPrieto Ortiz, Flavio Augusto
dc.contributor.authorPenagos Espinel, Oscar Fernando
dc.contributor.researcherVelasquez Hernandez Carlos Alberto
dc.date.accessioned2022-03-08T16:44:42Z
dc.date.available2022-03-08T16:44:42Z
dc.date.issued2021
dc.descriptionilustraciones, graficasspa
dc.description.abstractLa antracnosis es una enfermedad que afecta una gran cantidad de plantas, es producida principalmente por el hongo Colletotrichum, dada su fácil propagación por el aire, su abundante presencia en climas cálidos o en temporadas de alta temperatura como países con estaciones de verano y primavera, y su control mediante agentes químicos, genera la muerte de numerosas plantas y con ello grandes pérdidas económicas afectando principalmente a agricultores. El objetivo de este proyecto es evaluar el uso de imágenes hiperespectrales como apoyo a la detección de antrancnosis, para ello se hace uso de métodos de clasificación tradicionales como LDA y KNN y enfocados en datos espectrales como SAM, además del reductor de dimensionalidad PCA con el fin de encontrar la mínima cantidad de bandas espectrales necesarias para detectar la presencia del patógeno. (Texto tomado de la fuente)spa
dc.description.abstractAnthracnose is a disease that a affects a large number of plants, it is mainly produced by the fungus Colletotrichum, given its easy propagation through the air, its abundant presence in hot climates or in seasons of high temperature such as summer and spring seasons, and its control by chemical agents, generates the death of numerous plants and with it great economic losses affecting mainly farmers. The objective of this project is to evaluate the use of hyperspectral images to support the detection of anthracnose, using traditional classification methods such as LDA and KNN and focused on spectral data such as SAM, in addition to the dimensionality reducer PCA in order to find the minimum number of spectral bands necessary to detect the presence of the pathogen.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Ingeniería Electrónicaspa
dc.format.extentvi, 39 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/81152
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.departmentDepartamento de Ingeniería Eléctrica y Electrónicaspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Electrónicaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/spa
dc.subject.ddc530 - Física::537 - Electricidad y electrónicaspa
dc.subject.lembHONGOS-ECOLOGIAspa
dc.subject.lembECOLOGIA VEGETALspa
dc.subject.lembINDUSTRIA DE EQUIPOS PARA DIAGNOSTICO POR IMAGENESspa
dc.subject.proposalImágenes hiperespectralesspa
dc.subject.proposalAntracnosisspa
dc.subject.proposalMétodos de clasificación supervisadaspa
dc.subject.proposalPrincipal Component Analysiseng
dc.subject.proposalSpectral Angle Mappereng
dc.subject.proposalk-Nearest Neighboreng
dc.subject.proposalLinear discriminant analysiseng
dc.subject.proposalHyperspectral Imageeng
dc.subject.proposalAnthracnoseeng
dc.subject.proposalUnsupervised Classi cation Methodseng
dc.titleDetección de antracnosis foliar en plantas de mango por medio de análisis de imágenes hiperespectralesspa
dc.title.translatedDetection of foliar anthracnose on mango plants by hyperspectral image analysiseng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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