activity
20172021
most citedUsing GAN to Enhance the Accuracy of Indoor Human Activity Recognition

21 citations · 21 across the 2 of their papers we have counts for

collaborators

5 papers

cs.NI2021

Generative Adversarial Networks (GANs) in Networking: A Comprehensive Survey & Evaluation

Hojjat Navidan, Parisa Fard Moshiri, Mohammad Nabati +4

Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute an extensively researched machine learning sub-field for the creation of synthetic data t…

eess.SP2021

Using Synthetic Data to Enhance the Accuracy of Fingerprint-Based Localization: A Deep Learning Approach

Mohammad Nabati, Hojjat Navidan, Reza Shahbazian +2

Human-centered data collection is typically costly and implicates issues of privacy. Various solutions have been proposed in the literature to reduce this cost, such as crowdsource…

eess.SP202021 cited

Using GAN to Enhance the Accuracy of Indoor Human Activity Recognition

Parisa Fard Moshiri, Hojjat Navidan, Reza Shahbazian +2

Indoor human activity recognition (HAR) explores the correlation between human body movements and the reflected WiFi signals to classify different activities. By analyzing WiFi sig…

cs.NI2019

Delay Analysis in Full-Duplex Heterogeneous Cellular Networks

Leila Marandi, Mansour Naslcheraghi, Seyed Ali Ghorashi +1

Heterogeneous networks (HetNets) as a combination of macro cells and small cells are used to increase the cellular network's capacity, and present a perfect solution for high-speed…

cs.IT2017

Performance Analysis of Inband FD-D2D Communications with Imperfect SI Cancellation for Wireless Video Distribution

Mansour Naslcheraghi, Seyed Ali Ghorashi, Mohammad Shikh-Bahaei

Tremendous growing demand for high data rate services is the main driver for increasing traffic in wireless cellular networks. Device-to-Device (D2D) communications have recently b…