Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Vahab Khoshdel"'
Publikováno v:
IEEE Access, Vol 8, Pp 182092-182104 (2020)
A deep learning approach is proposed for performing tissue-type classification of tomographic microwave and ultrasound property images of the breast. The approach is based on a convolutional neural network (CNN) utilizing the U-net architecture that
Externí odkaz:
https://doaj.org/article/cd038258e25945c492d7d6216a247b2b
Publikováno v:
Journal of Imaging, Vol 6, Iss 8, p 80 (2020)
A deep learning technique to enhance 3D images of the complex-valued permittivity of the breast obtained via microwave imaging is investigated. The developed technique is an extension of one created to enhance 2D images. We employ a 3D Convolutional
Externí odkaz:
https://doaj.org/article/da2c21402b314c18b121c737bd150eaa
Publikováno v:
Sensors, Vol 19, Iss 18, p 4050 (2019)
We present a deep learning method used in conjunction with dual-modal microwave-ultrasound imaging to produce tomographic reconstructions of the complex-valued permittivity of numerical breast phantoms. We also assess tumor segmentation performance u
Externí odkaz:
https://doaj.org/article/b1ddf76281ef4bedbec7f5965e28c14d
Publikováno v:
Intelligent Automation & Soft Computing. 34:279-294
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c6e0770796d5c4f40fa75f52af31f5b
https://doi.org/10.32604/iasc.2022.023717
https://doi.org/10.32604/iasc.2022.023717
Publikováno v:
Neural Computing and Applications. 33:13467-13479
In this paper, a multi-branch deep convolutional fusion architecture is proposed to solve electromagnetic inverse scattering problems. The conventional methods for solving inverse problems face various challenges, including strong ill-conditioning, e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52dcbeec94dafe10623524fe65e1299e
https://doi.org/10.1007/s00521-021-05970-3
https://doi.org/10.1007/s00521-021-05970-3
Publikováno v:
IEEE Journal on Multiscale and Multiphysics Computational Techniques. 6:62-72
Combined ultrasound-microwave breast imaging requires a mechanism to guide one imaging modality using the other. To this end, a convolutional neural network (CNN) is proposed for the mapping of ultrasound property images to dielectric property images
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94667c82a1b5e1c8b6ee7f356155164a
https://doi.org/10.1109/jmmct.2021.3076827
https://doi.org/10.1109/jmmct.2021.3076827
Publikováno v:
IEEE Access, Vol 8, Pp 182092-182104 (2020)
A deep learning approach is proposed for performing tissue-type classification of tomographic microwave and ultrasound property images of the breast. The approach is based on a convolutional neural network (CNN) utilizing the U-net architecture that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9c4ba1b8614b5e563de3521572b3e79
https://doi.org/10.1109/access.2020.3027805
https://doi.org/10.1109/access.2020.3027805
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f683c4e41e8d9cb78666a0596ce3553d
https://doi.org/10.23919/ursigass51995.2021.9560264
https://doi.org/10.23919/ursigass51995.2021.9560264
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b91d972a5aea97b0c5d1c7a3235a30f9
https://doi.org/10.23919/ursigass49373.2020.9232216
https://doi.org/10.23919/ursigass49373.2020.9232216
Autor:
Vahab Khoshdel, Alireza Akbarzadeh
Publikováno v:
Industrial Robot: An International Journal. 45:416-423
PurposeThis paper aims to present an application of design of experiments techniques to determine the optimized parameters of artificial neural networks (ANNs), which are used to estimate human force from Electromyogram (sEMG) signals for rehabilitat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9cf55c6cae7c18ca186b682753fbebc
https://doi.org/10.1108/ir-10-2017-0190
https://doi.org/10.1108/ir-10-2017-0190