Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Mrinal Mohit"'
Publikováno v:
BMC Oral Health, Vol 17, Iss 1, Pp 1-10 (2017)
Abstract Background Significant numbers of adults and children have untreated plaque due to poor oral hygiene and consequently suffer from associate dental and systemic diseases. Methods A handheld device equipped with 405 nm light-emitting diodes wa
Externí odkaz:
https://doaj.org/article/b8fc4a541c474e4ba5fbc5c2d6d51afe
Publikováno v:
EMNLP
Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dee2bcc797e721d04ae9b7b9e59ab719
http://arxiv.org/abs/1810.07942
http://arxiv.org/abs/1810.07942
Autor:
Pratik Shah, Otkrist Gupta, Mrinal Mohit, S. V. Subramanian, Vincent Patalano, Gregory Yauney, Rikin Merchant
Publikováno v:
BMJ Open
Objectives Technology-enabled non-invasive diagnostic screening (TES) using smartphones and other point-of-care medical devices was evaluated in conjunction with conventional routine health screenings for the primary care screening of patients. Desig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73381d759a967d45dd0c841e89b82709
http://europepmc.org/articles/PMC5914894
http://europepmc.org/articles/PMC5914894
Scene context is more than a Bayesian prior: Competitive vehicle detection with restricted detectors
Publikováno v:
IEEE International Symposium on Intelligent Vehicles(IV)
IEEE International Symposium on Intelligent Vehicles(IV), May 2014, Detroit, United States. pp.1358-1364, ⟨10.1109/IVS.2014.6856542⟩
Intelligent Vehicles Symposium
IEEE International Symposium on Intelligent Vehicles(IV), May 2014, Detroit, United States. pp.1358-1364, ⟨10.1109/IVS.2014.6856542⟩
Intelligent Vehicles Symposium
International audience; We present a new approach for making use of scene or situation context in object detection, aiming for state-of-the-art performance while dramatically reducing computa-tional cost. While existing approaches are inspired by Bay
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c89ffee8c0f2eeda912abacaef29bb82
https://hal.inria.fr/hal-01098707/document
https://hal.inria.fr/hal-01098707/document