209 citations · 324 across the 42 of their papers we have counts for
4 papers · 1 filter
Attribution-Guided Model Rectification of Unreliable Neural Network Behaviors
Peiyu Yang, Naveed Akhtar, Jiantong Jiang +1
The performance of neural network models deteriorates due to their unreliable behavior on non-robust features of corrupted samples. Owing to their opaque nature, rectifying models…
On Transfer-based Universal Attacks in Pure Black-box Setting
Mohammad A. A. K. Jalwana, Naveed Akhtar, Ajmal Mian +2
Despite their impressive performance, deep visual models are susceptible to transferable black-box adversarial attacks. Principally, these attacks craft perturbations in a target m…
Regulating Model Reliance on Non-Robust Features by Smoothing Input Marginal Density
Peiyu Yang, Naveed Akhtar, Mubarak Shah +1
Trustworthy machine learning necessitates meticulous regulation of model reliance on non-robust features. We propose a framework to delineate and regulate such features by attribut…
Orthogonal Deep Models As Defense Against Black-Box Attacks
Mohammad A. A. K. Jalwana, Naveed Akhtar, Mohammed Bennamoun +1
Deep learning has demonstrated state-of-the-art performance for a variety of challenging computer vision tasks. On one hand, this has enabled deep visual models to pave the way for…