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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampLopes, Renato da Rocha-
dc.typeEditorialpt_BR
dc.titleSubsurface exploration: recent advances in geo-signal processing, interpretation, and learningpt_BR
dc.contributor.authorAlRegib, Ghassan-
dc.contributor.authorFomel, Sergey-
dc.contributor.authorLopes, Renato-
dc.subjectGeofísicapt_BR
dc.subjectSensoriamento remotopt_BR
dc.subject.otherlanguageGeophysicspt_BR
dc.subject.otherlanguageRemote sensingpt_BR
dc.description.abstractThe articles in this special section focus on subsurface exploration using new geo-signaling technologies. For centuries, humans have been exploring the subsurface structure of planet Earth. Several Earth geophysical applications, such as mining, earthquake studies, and oil and gas exploration, have driven research that produced, over the years, ground-breaking theories and innovative technologies that image Earth’s subsurface. The pursuit is ongoing with an increasing desire to have higher-resolution subsurface models and images. Signal processing, data interpretation, and modeling have been the cornerstones of such innovations. In recent years, there have been advances in technologies and requirements that demand the utilization of advanced signal processing and machine-learning theories and algorithms. For example, the wide- and full-azimuth acquisition technologies have proven to be instrumental in providing high-resolution subsurface imagespt_BR
dc.relation.ispartofIEEE Signal processing magazinept_BR
dc.relation.ispartofabbreviationIEEE Signal process. mag.pt_BR
dc.publisher.cityPiscataway, NJpt_BR
dc.publisher.countryEstados Unidospt_BR
dc.publisherInstitute of Electrical and Electronics Engineerspt_BR
dc.date.issued2018-
dc.date.monthofcirculationMar.pt_BR
dc.language.isoengpt_BR
dc.description.volume35pt_BR
dc.description.issuenumber2pt_BR
dc.description.firstpage16pt_BR
dc.description.lastpage18pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn1053-5888pt_BR
dc.identifier.eissn1558-0792pt_BR
dc.identifier.doi10.1109/MSP.2017.2786838pt_BR
dc.identifier.urlhttps://ieeexplore.ieee.org/document/8310688pt_BR
dc.date.available2020-09-15T18:17:38Z-
dc.date.accessioned2020-09-15T18:17:38Z-
dc.description.provenanceSubmitted by Mariana Aparecida Azevedo (mary1@unicamp.br) on 2020-09-15T18:17:38Z No. of bitstreams: 0. Added 1 bitstream(s) on 2021-01-08T19:03:14Z : No. of bitstreams: 1 000427512300004.pdf: 245101 bytes, checksum: 53e6cdc114caec7fef2fa389402a2c03 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-09-15T18:17:38Z (GMT). No. of bitstreams: 0 Previous issue date: 2018en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/349339-
dc.contributor.departmentDepartamento de Comunicaçõespt_BR
dc.contributor.unidadeFaculdade de Engenharia Elétrica e de Computaçãopt_BR
dc.subject.keywordGeospatial analysispt_BR
dc.identifier.source000427512300004pt_BR
dc.creator.orcid0000-0003-2618-5499pt_BR
dc.type.formEditorialpt_BR
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