Zobrazeno 1 - 4
of 4
pro vyhledávání: '"David Mascharka"'
Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning
Publikováno v:
CVPR
Visual question answering requires high-order reasoning about an image, which is a fundamental capability needed by machine systems to follow complex directives. Recently, modular networks have been shown to be an effective framework for performing v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd927068629dc7fc7f57c491cb9a37ab
https://doi.org/10.1109/cvpr.2018.00519
https://doi.org/10.1109/cvpr.2018.00519
Autor:
Don L. Hampton, Frank D. Lind, Joshua Semeter, Will Rogers, Victor Pankratius, David Mascharka, Philip J. Erickson, Anthea J. Coster, Timothy Morin
Publikováno v:
The International Technical Meeting of the The Institute of Navigation.
The Mahali Space Weather Monitoring project, funded by the U. S. National Science Foundation, has a research goal of forming a global space weather monitoring network based on an architecture that utilizes GNSS receivers powered by solar panels, wire
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::893fe8b5981a9c54ddbf25dd863834a6
https://doi.org/10.33012/2016.13470
https://doi.org/10.33012/2016.13470
Autor:
Katie Roth, Timothy Urness, Adina M. Kilpatrick, Rachel Davis, Paxten Johnson, Leah Robison, David Mascharka, Joel Venzke
Publikováno v:
Volume 13, Issue 1. 13
Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for determining three-dimensional structures of biomolecules, including proteins. The protein structure determination process requires measured NMR values to be assigned to specific a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4662bd433ae8c7179834eba985a0baf9
https://doi.org/10.33697/ajur.2016.005
https://doi.org/10.33697/ajur.2016.005
Autor:
Eric D. Manley, David Mascharka
Publikováno v:
CCNC
In this paper we investigate the problem of localizing a mobile device based on readings from its sensors utilizing machine learning methodologies. We consider a real-world environment, collect a dense set of 3110 datapoints, and examine the performa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae560d9b7003046ea08f876d258d780a
https://doi.org/10.1109/ccnc.2016.7444919
https://doi.org/10.1109/ccnc.2016.7444919