Multispectral images segmentation using fuzzy probabilistic local cluster for unsupervised clustering

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dc.contributor.authorMantilla, Luis
dc.contributor.authorYari Ramos, Yessenia Deysi
dc.date.accessioned2019-01-29T22:19:49Z
dc.date.available2019-01-29T22:19:49Z
dc.date.issued2018
dc.description.abstractIn Pattern Recognition there are many algorithms it try to solve the problem of grouping objects of the same type, this is called clustering, however the task of dividing these lies not only in the objective function, but also the methodology used to calculate the similarity between objects. Because multispectral images contain information that has low statistical separation and a large amount of data it is necessary to enter local information. In this paper, the use of the Gaussian dispersion equation is proposed in order to calculate the contribution of each sample to the sample analyzed. The results show that the integration of local weights within the clustering model decreases the entropy of each group generated. © 2017 IEEE.es_PE
dc.description.uriTrabajo de investigaciónes_PE
dc.identifier.doihttps://doi.org/10.1109/LA-CCI.2017.8285729es_PE
dc.identifier.isbnurn:isbn:9781538637340es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12590/15758
dc.language.isoenges_PE
dc.publisherInstitute of Electrical and Electronics Engineers Inc.es_PE
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85050374001&doi=10.1109%2fLA-CCI.2017.8285729&partnerID=40&md5=4cc30d1d91d8876342f2618ab0975d04es_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.sourceRepositorio Institucional - UCSPes_PE
dc.sourceUniversidad Católica San Pabloes_PE
dc.sourceScopuses_PE
dc.subjectArtificial intelligencees_PE
dc.subjectClassification (of information)es_PE
dc.subjectPattern recognitiones_PE
dc.subjectGaussian dispersionses_PE
dc.subjectMultispectral imageses_PE
dc.subjectObjective functionses_PE
dc.subjectSatellite imageses_PE
dc.subjectSimilarity between objectses_PE
dc.subjectUnsupervised classificationes_PE
dc.subjectUnsupervised clusteringes_PE
dc.subjectWeight informationes_PE
dc.subjectImage segmentationes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.02.00es_PE
dc.titleMultispectral images segmentation using fuzzy probabilistic local cluster for unsupervised clusteringes_PE
dc.typeinfo:eu-repo/semantics/conferenceObject
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