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of 10
pro vyhledávání: '"Keeley Edwards"'
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:
2023 17th European Conference on Antennas and Propagation (EuCAP).
Publikováno v:
Progress In Electromagnetics Research. 175:1-11
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:
2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS).
A recently developed neural network architecture for recovering the radius, height, and bulk complex-valued permittivity of the fibroglandular region of a human breast model from microwave measurements is extended to multiple frequencies. Results are
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
Publikováno v:
Electronics
Volume 10
Issue 6
Electronics, Vol 10, Iss 674, p 674 (2021)
Volume 10
Issue 6
Electronics, Vol 10, Iss 674, p 674 (2021)
A two-stage workflow for detecting and monitoring tumors in the human breast with an inverse scattering-based technique is presented. Stage 1 involves a phaseless bulk-parameter inference neural network that recovers the geometry and permittivity of
Autor:
Keeley Edwards, Graham Paley, Inga Janmere, Catherine Reid, Amy Danks, Helen Rawse, Miriam Fearon
Publikováno v:
Mental Health Practice. 16:10-15
Autor:
Paley, Graham, Danks, Amy, Edwards, Keeley, Reid, Catherine, Fearon, Miriam, Janmere, Inga, Rawse, Helen
Publikováno v:
Mental Health Practice; Apr2013, Vol. 16 Issue 7, p10-15, 6p
Autor:
Edwards, Keeley, Khoshdel, Vahab, Asefi, Mohammad, LoVetri, Joe, Gilmore, Colin, Jeffrey, Ian, Solimene, Raffaele, Cennamo, Nunzio, Maisto, Maria Antonia
Publikováno v:
Electronics (2079-9292); Mar2021, Vol. 10 Issue 6, p674, 1p