collaborators

5 papers

eess.SP2021

Simultaneous estimation of wall and object parameters in TWR using deep neural network

Fardin Ghorbani, Hossein Soleimani

This paper presents a deep learning model for simultaneously estimating target and wall parameters in Through-the-Wall Radar. In this work, we consider two modes: single-target and…

cs.LG2021

A deep learning approach for inverse design of the metasurface for dual-polarized waves

Fardin Ghorbani, Javad Shabanpour, Sina Beyraghi +3

Compared to the conventional metasurface design, machine learning-based methods have recently created an inspiring platform for an inverse realization of the metasurfaces. Here, we…

eess.SP2021

Deep neural network-based automatic metasurface design with a wide frequency range

Fardin Ghorbani, Sina Beyraghi, Javad Shabanpour +3

Beyond the scope of conventional metasurface which necessitates plenty of computational resources and time, an inverse design approach using machine learning algorithms promises an…

physics.optics2021

Implementation of conformal digital metasurfaces for THz polarimetric sensing

Javad Shabanpour, Sina Beyraghi, Fardin Ghorbani +1

Monitoring and controlling the state of polarization of electromagnetic waves is of significant interest for various basic and practical applications such as linear position sensin…

eess.SP2020

EEGsig: an open-source machine learning-based toolbox for EEG signal processing

Fardin Ghorbani, Javad Shabanpour, Sepideh Monjezi +3

In the quest to realize a comprehensive EEG signal processing framework, in this paper, we demonstrate a toolbox and graphic user interface, EEGsig, for the full process of EEG sig…