2 citations · 3 across the 12 of their papers we have counts for
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Exploring the Robustness and Transferability of Patch-Based Adversarial Attacks in Quantized Neural Networks
Amira Guesmi, Bassem Ouni, Muhammad Shafique
Quantized neural networks (QNNs) are increasingly used for efficient deployment of deep learning models on resource-constrained platforms, such as mobile devices and edge computing…
Navigating Threats: A Survey of Physical Adversarial Attacks on LiDAR Perception Systems in Autonomous Vehicles
Amira Guesmi, Muhammad Shafique
Autonomous vehicles (AVs) rely heavily on LiDAR (Light Detection and Ranging) systems for accurate perception and navigation, providing high-resolution 3D environmental data that i…
Representing Neural Network Layers as Linear Operations via Koopman Operator Theory
Nishant Suresh Aswani, Saif Eddin Jabari, Muhammad Shafique
The strong performance of simple neural networks is often attributed to their nonlinear activations. However, a linear view of neural networks makes understanding and controlling n…
Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach
Amira Guesmi, Nishant Suresh Aswani, Muhammad Shafique
Adversarial attacks pose a significant challenge to deploying deep learning models in safety-critical applications. Maintaining model robustness while ensuring interpretability is…
Examining Changes in Internal Representations of Continual Learning Models Through Tensor Decomposition
Nishant Suresh Aswani, Amira Guesmi, Muhammad Abdullah Hanif +1
Continual learning (CL) has spurred the development of several methods aimed at consolidating previous knowledge across sequential learning. Yet, the evaluations of these methods h…
SSAP: A Shape-Sensitive Adversarial Patch for Comprehensive Disruption of Monocular Depth Estimation in Autonomous Navigation Applications
Amira Guesmi, Muhammad Abdullah Hanif, Ihsen Alouani +2
Monocular depth estimation (MDE) has advanced significantly, primarily through the integration of convolutional neural networks (CNNs) and more recently, Transformers. However, con…
Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks
Nandish Chattopadhyay, Amira Guesmi, Muhammad Shafique
Adversarial patch attacks pose a significant threat to the practical deployment of deep learning systems. However, existing research primarily focuses on image pre-processing defen…