dc.contributor.author | Corcoran, Peter | |
dc.contributor.author | Lemley, Joseph | |
dc.contributor.author | Costache, Claudia | |
dc.contributor.author | Varkarakis, Viktor | |
dc.date.accessioned | 2019-10-03T08:59:53Z | |
dc.date.available | 2019-10-03T08:59:53Z | |
dc.date.issued | 2019-09-02 | |
dc.identifier.citation | Corcoran, P., Lemley, J., Costache, C., & Varkarakis, V. (2019). Deep Learning for Consumer Devices and Services 2—AI Gets Embedded at the Edge. IEEE Consumer Electronics Magazine, 8(5), 10-19. doi: 10.1109/MCE.2019.2923042 | en_IE |
dc.identifier.issn | 2162-2248 | |
dc.identifier.uri | http://hdl.handle.net/10379/15482 | |
dc.description.abstract | The recent explosive growth of deep learning is enabling a new generation of intelligent consumer devices. Specialized deep learning inference now provides data analysis capabilities that once required an active cloud connection, while reducing latency and enhancing data privacy. This paper addresses current progress in Edge artificial intelligence (AI) technology in several consumer contexts including privacy, biometrics, eye gaze, driver monitoring systems, and more. New developments and challenges in edge hardware and emerging opportunities are identified. Our previous article, "Deep learning for consumer devices and services," introduced many of the basics of deep learning and AI. In this paper, we explore the current paradigm shift of AI from the data center into CE devices-"Edge-AI." | en_IE |
dc.description.sponsorship | This work was supported in part by the SFI
Strategic Partnership Program by Science Foundation Ireland and FotoNation, Ltd., under Project 13/SPP/I2868 on Next Generation Imaging
for Smartphone and Embedded Platforms, and
in part by an Irish Research Council Employment-Based Programme Award under Project
EBPPG/2016/280. | en_IE |
dc.format | application/pdf | en_IE |
dc.language.iso | en | en_IE |
dc.publisher | IEEE | en_IE |
dc.relation.ispartof | IEEE Consumer Electronics Magazine | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.subject | LIVENESS DETECTION | en_IE |
dc.subject | FEATURES | en_IE |
dc.subject | AUTHENTICATION | en_IE |
dc.subject | SEGMENTATION | en_IE |
dc.subject | PERFORMANCE | en_IE |
dc.subject | GENERATION | en_IE |
dc.subject | BIOMETRICS | en_IE |
dc.subject | INTERNET | en_IE |
dc.subject | NETWORK | en_IE |
dc.subject | THINGS | en_IE |
dc.title | Deep learning for consumer devices and services 2-AI gets embedded at the edge | en_IE |
dc.type | Article | en_IE |
dc.date.updated | 2019-09-29T12:39:52Z | |
dc.identifier.doi | 10.1109/MCE.2019.2923042 | |
dc.local.publishedsource | https://dx.doi.org/10.1109/MCE.2019.2923042 | en_IE |
dc.description.peer-reviewed | peer-reviewed | |
dc.contributor.funder | Science Foundation Ireland | en_IE |
dc.contributor.funder | FotoNation, Ltd | en_IE |
dc.contributor.funder | Irish Research Council | en_IE |
dc.internal.rssid | 17709402 | |
dc.local.contact | Peter Corcoran, Electrical & Electronic Eng, Room 3041, Engineering Building, Nui Galway. 2764 Email: peter.corcoran@nuigalway.ie | |
dc.local.copyrightchecked | Yes | |
dc.local.version | ACCEPTED | |
dcterms.project | info:eu-repo/grantAgreement/SFI/SFI Strategic Partnership Programme/13/SPP/I2868/IE/Next Generation Imaging for Smartphone and Embedded Platforms/ | en_IE |
nui.item.downloads | 503 | |