Publicación:
Multispectral images segmentation using fuzzy probabilistic local cluster for unsupervised clustering

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dc.contributor.author Mantilla S.C.L. es_PE
dc.contributor.author Yari Y. es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2018
dc.description The authors would like to CONCYTEC (Consejo Nacional de Ciencia, Tecnolog ıa e Innovacion Tecnoloogica ), FONDE- ´ CYT (Fondo Nacional de Desarrollo Cient´ıfico y Tecnologico) ´and ANA (Autoridad Nacional del Agua) for satellite imagesand supporting this project
dc.description.abstract In 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.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1109/LA-CCI.2017.8285729
dc.identifier.isbn 9781538637340
dc.identifier.scopus 2-s2.0-85050374001
dc.identifier.uri https://hdl.handle.net/20.500.12390/705
dc.language.iso eng
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof 2017 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2017 - Proceedings
dc.rights info:eu-repo/semantics/openAccess
dc.subject Weight information
dc.subject Artificial intelligence es_PE
dc.subject Classification (of information) es_PE
dc.subject Pattern recognition es_PE
dc.subject Gaussian dispersions es_PE
dc.subject Multispectral images es_PE
dc.subject Objective functions es_PE
dc.subject Satellite images es_PE
dc.subject Similarity between objects es_PE
dc.subject Unsupervised classification es_PE
dc.subject Unsupervised clustering es_PE
dc.subject Image segmentation es_PE
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#1.02.00
dc.title Multispectral images segmentation using fuzzy probabilistic local cluster for unsupervised clustering
dc.type info:eu-repo/semantics/conferenceObject
dspace.entity.type Publication
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
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