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dc.contributor.authorVillalón-Turrubiates, Iván E.
dc.date.accessioned2016-04-21T18:16:40Z
dc.date.accessioned2023-03-10T16:54:33Z
dc.date.available2016-04-21T18:16:40Z
dc.date.available2023-03-10T16:54:33Z
dc.date.issued2015-07
dc.identifier.citationIvan E. Villalon-Turrubiates, “A Dynamical Model to Classify the Content of Multitemporal Images employing Distributed Computing Techniques”, in Proceedings of the 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MULTITEMP), IEEE, Annecy Francia, 2015.es
dc.identifier.isbn978-1-4799-7929-5
dc.identifier.urihttps://hdl.handle.net/20.500.12032/69500
dc.descriptionAn intelligent post-processing paradigm based on the use of a dynamical filtering technique modified to enhance the reconstruction quality of remote sensing indexes using multitemporal images and distributed computing techniques is proposed. As a matter of particular study, a robust algorithm is reported for the analysis of the dynamic behavior of geophysical signatures extracted from remotely sensed scenes. The simulation results prove the efficiency of the proposed technique along with the computational implementation based on a big-data framework using distributed processing.es
dc.description.sponsorshipITESO, A.C.es
dc.language.isoenges
dc.publisherInformation Resources Management Associationes
dc.relation.ispartofseriesInternational Workshop on the Analysis of Multitemporal Remote Sensing Images (MULTITEMP);8th
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectRemote Sensinges
dc.subjectMultispectral Imaginges
dc.subjectGeodynamicses
dc.subjectDistributed Computinges
dc.titleA Dynamical Model to Classify the Content of Multitemporal Images employing Distributed Computing Techniqueses
dc.typeinfo:eu-repo/semantics/conferencePaperes


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