5 citations · 9 across the 5 of their papers we have counts for
5 papers
Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory Overfitting Challenge in Continual Learning
Hikmat Khan, Ghulam Rasool, Nidhal Carla Bouaynaya
Continual learning focuses on learning non-stationary data distribution without forgetting previous knowledge. Rehearsal-based approaches are commonly used to combat catastrophic f…
Deep Ensemble for Rotorcraft Attitude Prediction
Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool +3
Historically, the rotorcraft community has experienced a higher fatal accident rate than other aviation segments, including commercial and general aviation. Recent advancements in…
The Importance of Robust Features in Mitigating Catastrophic Forgetting
Hikmat Khan, Nidhal C. Bouaynaya, Ghulam Rasool
Continual learning (CL) is an approach to address catastrophic forgetting, which refers to forgetting previously learned knowledge by neural networks when trained on new tasks or d…
Comparative Analysis of State-of-the-Art Deep Learning Models for Detecting COVID-19 Lung Infection from Chest X-Ray Images
Zeba Ghaffar, Pir Masoom Shah, Hikmat Khan +5
The ongoing COVID-19 pandemic has already taken millions of lives and damaged economies across the globe. Most COVID-19 deaths and economic losses are reported from densely crowded…
Susceptibility of Continual Learning Against Adversarial Attacks
Hikmat Khan, Pir Masoom Shah, Syed Farhan Alam Zaidi +2
Recent continual learning approaches have primarily focused on mitigating catastrophic forgetting. Nevertheless, two critical areas have remained relatively unexplored: 1) evaluati…