Real-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computing

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dc.contributor.authorShkvarko, Yuriy
dc.contributor.authorVillalón-Turrubiates, Iván E.
dc.date.accessioned2016-04-04T21:04:34Z
dc.date.available2016-04-04T21:04:34Z
dc.date.issued2005
dc.descriptionThe robustified numerical technique for real-time sensor array reconstructive image processing is developed as required for remote sensing imaging with large scale array/synthesized array radars. The addressed technique is designed via performing the regularized robustification of the fused Bayesian-regularization imaging method aggregated with the efficient real-time numerical implementation scheme that employs the neural network computing.es
dc.description.sponsorshipCINVESTAVes
dc.identifier.citationY. Shkvarko & I.E. Villalón-Turrubiate (2005), “Real-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computing”. Proceedings of the 17th International Association for Mathematics and Computers in Simulation (IMACS) World Congress, París, Francia.es
dc.identifier.urihttp://hdl.handle.net/11117/3234
dc.language.isoenges
dc.publisherAssociation for Mathematics and Computers in Simulationes
dc.relation.ispartofseriesIMACS;17h
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectImage Reconstructiones
dc.subjectRegularizationes
dc.subjectNeural Networkses
dc.titleReal-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computinges
dc.typeinfo:eu-repo/semantics/conferencePaperes
rei.peerreviewedYeses
rei.revisorIMACS

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