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dc.contributor.authorGómez-Sanchís, Juan
dc.contributor.authorBlasco, José
dc.contributor.authorMoltó, Enrique
dc.contributor.authorCamps-Valls, G.
dc.date.accessioned2017-06-01T10:12:05Z
dc.date.available2017-06-01T10:12:05Z
dc.date.issued2007
dc.identifier.citationGomez, J., Blasco, J., Moltó, E., Camps-Valls, G. (2007). Hyperspectral detection of citrus damage with Mahalanobis kernel classifier. Electronics Letters, 43(20), 1082-1084.
dc.identifier.issn0013-5194
dc.identifier.urihttp://hdl.handle.net/20.500.11939/5293
dc.description.abstractPresented is a full computer vision system for the identification of post-harvest damage in citrus packing houses. The method is based on the combined use of hyperspectral images and the Mahalanobis kernel classifier. More accurate and reliable results compared to other methods are obtained in several scenarios and acquired images.
dc.language.isoen
dc.titleHyperspectral detection of citrus damage with Mahalanobis kernel classifier
dc.typearticle
dc.authorAddressInstituto Valenciano de Investigaciones Agrarias (IVIA), Carretera CV-315, Km. 10’7, 46113 Moncada (Valencia), Españaes
dc.date.issuedFreeFormSEP 27 2007
dc.entidadIVIACentro de Agroingeniería
dc.identifier.doi10.1049/el:20070906
dc.journal.abbreviatedTitleElectron.Lett.
dc.journal.issueNumber20
dc.journal.titleElectronics Letters
dc.journal.volumeNumber43
dc.page.final1084
dc.page.initial1082
dc.rights.accessRightsopenAccess
dc.source.typeImpreso
dc.type.hasVersionacceptedVersion


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