2 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
RCC-GAN: Regularized Compound Conditional GAN for Large-Scale Tabular Data Synthesis
Mohammad Esmaeilpour, Nourhene Chaalia, Adel Abusitta +3
This paper introduces a novel generative adversarial network (GAN) for synthesizing large-scale tabular databases which contain various features such as continuous, discrete, and b…
Improving Stability of LS-GANs for Audio and Speech Signals
Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges +2
In this paper we address the instability issue of generative adversarial network (GAN) by proposing a new similarity metric in unitary space of Schur decomposition for 2D represent…
Detection of Adversarial Attacks and Characterization of Adversarial Subspace
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propos…
A Robust Approach for Securing Audio Classification Against Adversarial Attacks
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
Adversarial audio attacks can be considered as a small perturbation unperceptive to human ears that is intentionally added to the audio signal and causes a machine learning model t…
Unsupervised Feature Learning for Environmental Sound Classification Using Weighted Cycle-Consistent Generative Adversarial Network
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper we propose a novel environmental sound classification approach incorporating unsupervised feature learning from codebook via spherical -Means++ algorithm and a new…