Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ryan Kruk"'
Autor:
Keeley Edwards, Nicholas Geddert, Kennedy Krakalovich, Ryan Kruk, Mohammad Asefi, Joe Lovetri, Colin Gilmore, Ian Jeffrey
Publikováno v:
IEEE Access, Vol 8, Pp 207182-207192 (2020)
We present a neural network architecture to determine the volume and complex permittivity of grain stored in metal bins. The neural networks output the grain height, cone angle and complex permittivity of the grain, using the input of experimental fi
Externí odkaz:
https://doaj.org/article/108e74ff1c264dfc8584d8cbcb14a12b
Publikováno v:
Remote Sensing, Vol 12, Iss 15, p 2486 (2020)
Accurate maps of ice concentration and ice type are needed to address increased interest in commercial marine transportation through the Arctic. RADARSAT-2 SAR imagery is the primary source of data used by expert ice analysts at the Canadian Ice Serv
Externí odkaz:
https://doaj.org/article/8c71ed265391457b85d84fdf2bebd945
Autor:
Nicholas Geddert, Ryan Kruk, Colin Gilmore, Joe LoVetri, Kennedy Krakalovich, Ian Jeffrey, Keeley Edwards, Mohammad Asefi
Publikováno v:
IEEE Access, Vol 8, Pp 207182-207192 (2020)
We present a neural network architecture to determine the volume and complex permittivity of grain stored in metal bins. The neural networks output the grain height, cone angle and complex permittivity of the grain, using the input of experimental fi
Publikováno v:
Remote Sensing, Vol 12, Iss 2486, p 2486 (2020)
Remote Sensing; Volume 12; Issue 15; Pages: 2486
Remote Sensing; Volume 12; Issue 15; Pages: 2486
Accurate maps of ice concentration and ice type are needed to address increased interest in commercial marine transportation through the Arctic. RADARSAT-2 SAR imagery is the primary source of data used by expert ice analysts at the Canadian Ice Serv
Autor:
Joe LoVetri, Ian Jeffrey, Colin Gilmore, Vahab Khoshdel, Ryan Kruk, Keeley Edwards, Kennedy Krakalovich
Publikováno v:
2020 XXXIIIrd General Assembly and Scientific Symposium of the International Union of Radio Science.
We present a machine learning work flow for the parametric inversion of grain bin measurements in which a neural network is trained solely on synthetic data for a unique bin geometry. This neural network can subsequently be used to rapidly obtain 4 i
Autor:
Neil Cyphert, Jennifer A. Willford, Aizenstein Howard, Richard O. Day, Matthew Zeglen, Bethany Ground, Nancy L. Day, Ryan Kruk
Publikováno v:
Neurotoxicology and Teratology. 31:248