Search Results for author: Hojjat Navidan

Found 3 papers, 1 papers with code

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

no code implementations10 May 2021 Hojjat Navidan, Parisa Fard Moshiri, Mohammad Nabati, Reza Shahbazian, Seyed Ali Ghorashi, Vahid Shah-Mansouri, David Windridge

Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute an extensively researched machine learning sub-field for the creation of synthetic data through deep generative modeling.

BIG-bench Machine Learning

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

1 code implementation5 May 2021 Mohammad Nabati, Hojjat Navidan, Reza Shahbazian, Seyed Ali Ghorashi, David Windridge

Various solutions have been proposed in the literature to reduce this cost, such as crowdsourced data collection, or the use of semi-supervised algorithms.

Using GAN to Enhance the Accuracy of Indoor Human Activity Recognition

no code implementations23 Apr 2020 Parisa Fard Moshiri, Hojjat Navidan, Reza Shahbazian, Seyed Ali Ghorashi, David Windridge

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

Generative Adversarial Network Human Activity Recognition

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