no code implementations • 29 Jun 2023 • Hikmat Khan, Nidhal C. Bouaynaya, Ghulam Rasoom
In this paper, we introduce the CL robust dataset and train four baseline models on both the standard and CL robust datasets.
no code implementations • 1 Feb 2023 • Yassine Barhoumi, Nidhal C. Bouaynaya, Ghulam Rasool
Hybrid CNNs and ViTs might provide the desired feature richness for developing accurate medical computer vision models
no code implementations • 10 Nov 2021 • Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya, Lyudmila Mihaylova
Learning in uncertain, noisy, or adversarial environments is a challenging task for deep neural networks (DNNs).
no code implementations • 10 Nov 2021 • Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya
We show that Bayesian neural networks automatically discover redundancy in model parameters, thus enabling self-compression, which is linked to the propagation of uncertainty through the layers of the network.
no code implementations • 10 Nov 2021 • Giuseppina Carannante, Dimah Dera, Nidhal C. Bouaynaya, Hassan M. Fathallah-Shaykh, Ghulam Rasool
Moreover, the uncertainty map of the proposed SUPER-Net associates low confidence (or equivalently high uncertainty) to patches in the test input images that are corrupted with noise, artifacts, or adversarial attacks.
no code implementations • 15 Aug 2021 • Daniel E. Cahall, Ghulam Rasool, Nidhal C. Bouaynaya, Hassan M. Fathallah-Shaykh
Magnetic resonance imaging (MRI) is routinely used for brain tumor diagnosis, treatment planning, and post-treatment surveillance.
1 code implementation • 30 Jun 2021 • Asim Waqas, Ghulam Rasool, Hamza Farooq, Nidhal C. Bouaynaya
The architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance.
no code implementations • 10 Jul 2018 • Nesrine Amor, Ghulam Rasool, Nidhal C. Bouaynaya
The real-world applications in signal processing generally involve estimating the system state or parameters in nonlinear, non-Gaussian dynamic systems.