dc.date.accessioned | 2020-10-29T18:59:52Z | |
dc.date.available | 2020-10-29T18:59:52Z | |
dc.date.issued | 2019-08-23 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/128254 | |
dc.description.abstract | Laboratory 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.sponsorship | New Jersey Office of Homeland Security and Preparedness | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | MIT Lincoln Laboratory | en_US |
dc.relation.ispartofseries | The Bulletin; | |
dc.rights | Attribution-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
dc.subject | Lincoln Laboratory | en_US |
dc.subject | Supercomputing | en_US |
dc.subject | LLSC | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.title | Video and Imagery Dataset to Drive Public Safety Capabilities | en_US |
dc.type | Article | en_US |