Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/50287
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dc.contributor.authorScavuzzo, Juan M.
dc.contributor.authorTrucco, Francisco
dc.contributor.authorEspinosa, Manuel
dc.contributor.authorTauro, Carolina B.
dc.contributor.authorAbril, Marcelo
dc.contributor.authorScavuzzo, Carlos M.
dc.contributor.authorFrery, Alejandro C.
dc.contributor.otherFrery, Alejandro
dc.date.accessioned2018-11-24T14:52:49Z-
dc.date.available2018-11-24T14:52:49Z-
dc.date.issued2018
dc.identifier.issn0001-706X
dc.identifier.urihttp://hdl.handle.net/10553/50287-
dc.publisher0001-706X
dc.relation.ispartofActa tropica (Print)
dc.sourceActa Tropica[ISSN 0001-706X],v. 185, p. 167-175
dc.titleModeling Dengue vector population using remotely sensed data and machine learning
dc.typeinfo:eu-repo/semantics/articlees
dc.typeArticlees
dc.identifier.doi10.1016/j.actatropica.2018.05.003
dc.identifier.scopus85047244084
dc.identifier.isi000440126000023
dcterms.isPartOfActa Tropica
dcterms.sourceActa Tropica[ISSN 0001-706X],v. 185, p. 167-175
dc.contributor.authorscopusid57201899056
dc.contributor.authorscopusid57201898846
dc.contributor.authorscopusid54888546500
dc.contributor.authorscopusid57195331554
dc.contributor.authorscopusid55378261000
dc.contributor.authorscopusid6603254408
dc.contributor.authorscopusid7003561251
dc.description.lastpage175
dc.description.firstpage167
dc.relation.volume185
dc.type2Artículoes
dc.identifier.wosWOS:000440126000023
dc.contributor.daisngid21980566
dc.contributor.daisngid18093544
dc.contributor.daisngid28149342
dc.contributor.daisngid3750230
dc.contributor.daisngid1791154
dc.contributor.daisngid1299295
dc.contributor.daisngid215914
dc.identifier.investigatorRIDA-8855-2008
dc.identifier.ulpgces
dc.description.sjr1,224
dc.description.jcr2,629
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.orcid0000-0002-8002-5341-
crisitem.author.fullNameC. Frery, Alejandro-
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