Visual Question Answering: A Deep Interactive Framework for Post-Disaster Management and Damage Assessment

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dc.contributor.authorSarkar, Argho
dc.contributor.authorRahnemoonfar, Maryam
dc.date.accessioned2021-08-16T20:05:32Z
dc.date.available2021-08-16T20:05:32Z
dc.date.issued2021-07-10
dc.descriptionClimate Change AIen_US
dc.description.urihttps://www.climatechange.ai/papers/icml2021/52/slides.pdfen_US
dc.format.extent13 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.genrepresentations (communicate events)en_US
dc.identifierdoi:10.13016/m2ylmc-gg8t
dc.identifier.citationSarkar, Argho; Rahnemoonfar, Maryam; Visual Question Answering: A Deep Interactive Framework for Post-Disaster Management and Damage Assessment; Climate Change AI, 10 July, 2021; https://www.climatechange.ai/papers/icml2021/52/slides.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/22470
dc.language.isoen_USen_US
dc.publisherClimate Change AIen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.titleVisual Question Answering: A Deep Interactive Framework for Post-Disaster Management and Damage Assessmenten_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-8545-0830en_US

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