Accelerated AI for Edge Computing

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dc.contributor.authorRahnemoonfar, Maryam
dc.date.accessioned2020-04-13T18:07:49Z
dc.date.available2020-04-13T18:07:49Z
dc.date.issued2020-02-25
dc.description.sponsorshipNSF Workshop on Smart Cyberinfrastructure, Feb. 25-27, 2020, Hyatt Regency, Crystal City, VAen_US
dc.description.urihttp://smartci.sci.utah.edu/images/whitepapers/5e5042ab0eb95-Accelerated_AI.pdfen_US
dc.format.extent3 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2dixz-3mko
dc.identifier.citationRahnemoonfar, Maryam; Accelerated AI for Edge Computing; NSF Workshop on Smart Cyberinfrastructure, Feb. 25-27, 2020, Hyatt Regency, Crystal City, VA; http://smartci.sci.utah.edu/images/whitepapers/5e5042ab0eb95-Accelerated_AI.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/18030
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty 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.
dc.subjectAnalysis of the big datasets collected by various sensorsen_US
dc.subjectreal-time analysis of data on Edgeen_US
dc.subjectlearning algorithmsen_US
dc.subjectdeep learningen_US
dc.titleAccelerated AI for Edge Computingen_US
dc.typeTexten_US

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