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dc.date.accessioned2020-10-29T18:59:52Z
dc.date.available2020-10-29T18:59:52Z
dc.date.issued2019-08-23
dc.identifier.urihttps://hdl.handle.net/1721.1/128254
dc.description.abstractLaboratory staff have been developing a computer vision dataset of operational and representative public safety scenarios. This dataset will enable technology development tailored to public safety scenarios, and includes operational images and videos from several organizations. They have labeled images so that machine learning algorithms can recognize a wide range of relevant public safety features in different environments. “The information within these images could improve various aspects of a response and recovery effort, such as damage assessment. Our dataset will enable the development of machine-learned analytics to prioritize and characterize images.”en_US
dc.description.sponsorshipNew Jersey Office of Homeland Security and Preparednessen_US
dc.language.isoen_USen_US
dc.publisherMIT Lincoln Laboratoryen_US
dc.relation.ispartofseriesThe Bulletin;
dc.rightsAttribution-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/us/*
dc.subjectLincoln Laboratoryen_US
dc.subjectSupercomputingen_US
dc.subjectLLSCen_US
dc.subjectArtificial Intelligenceen_US
dc.titleVideo and Imagery Dataset to Drive Public Safety Capabilitiesen_US
dc.typeArticleen_US


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