Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/355684
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampSilva, Ewerton Almeida-
dc.typeOutro documentopt_BR
dc.titleA change-driven image foveation approach for tracking plant phenologypt_BR
dc.contributor.authorSilva, Ewerton-
dc.contributor.authorTorres, Ricardo da S.-
dc.contributor.authorAlberton, Bruna-
dc.contributor.authorMorellato, Leonor Patricia C.-
dc.contributor.authorSilva, Thiago S. F.-
dc.subjectFenologia vegetalpt_BR
dc.subject.otherlanguagePlant phenologypt_BR
dc.description.abstractOne of the challenges in remote phenology studies lies in how to efficiently manage large volumes of data obtained as long-term sequences of high-resolution images. A promising approach is known as image foveation, which is able to reduce the computational resources used (i.e., memory storage) in several applications. In this paper, we propose an image foveation approach towards plant phenology tracking where relevant changes within an image time series guide the creation of foveal models used to resample unseen images. By doing so, images are taken to a space-variant domain where regions vary in resolution according to their contextual relevance for the application. We performed our validation on a dataset of vegetation image sequences previously used in plant phenology studiespt_BR
dc.relation.ispartofRemote sensingpt_BR
dc.relation.ispartofabbreviationRemote sens.pt_BR
dc.publisher.cityBaselpt_BR
dc.publisher.countrySuíçapt_BR
dc.publisherMDPIpt_BR
dc.date.issued2020-
dc.date.monthofcirculationApr.pt_BR
dc.language.isoengpt_BR
dc.description.volume12pt_BR
dc.description.issuenumber9pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.eissn2072-4292pt_BR
dc.identifier.doi10.3390/rs12091409pt_BR
dc.identifier.urlhttps://www.mdpi.com/2072-4292/12/9/1409pt_BR
dc.description.sponsorshipCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQpt_BR
dc.description.sponsorshipCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESpt_BR
dc.description.sponsorshipFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPpt_BR
dc.description.sponsordocumentnumber307560/2016-3; 311820/2018-2; 310144/2015-9pt_BR
dc.description.sponsordocumentnumber001pt_BR
dc.description.sponsordocumentnumber2014/12236-1; 2014/00215-0; 2015/24494-8; 2016/50250-1; 2016/01413-5; 2017/20945-0; 2013/50155-0; 2014/50715-9pt_BR
dc.date.available2021-02-12T13:59:51Z-
dc.date.accessioned2021-02-12T13:59:51Z-
dc.description.provenanceSubmitted by Susilene Barbosa da Silva (susilene@unicamp.br) on 2021-02-12T13:59:51Z No. of bitstreams: 0. Added 1 bitstream(s) on 2021-05-24T19:06:51Z : No. of bitstreams: 1 000543394000056.pdf: 10962754 bytes, checksum: ce855789b36f07223e41e76388497d91 (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-12T13:59:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2020en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/355684-
dc.contributor.departmentSem informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordFoveal modelpt_BR
dc.identifier.source000543394000056pt_BR
dc.creator.orcid0000-0003-4021-5906pt_BR
dc.type.formCartapt_BR
dc.identifier.articleid1409pt_BR
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