no code implementations • 12 Oct 2020 • Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper we propose a conditioning trick, called difference departure from normality, applied on the generator network in response to instability issues during GAN training.
no code implementations • 26 Aug 2020 • Raymel Alfonso Sallo, Mohammad Esmaeilpour, Patrick Cardinal
In this paper, we investigate the potential effect of the adversarially training on the robustness of six advanced deep neural networks against a variety of targeted and non-targeted adversarial attacks.
no code implementations • 12 Aug 2020 • Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges, Patrick Cardinal, Alessandro Lameiras Koerich
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 representations of audio and speech signals.