22 citations · 96 across the 18 of their papers we have counts for
7 papers · 1 filter
Scaling Model Checking for DNN Analysis via State-Space Reduction and Input Segmentation (Extended Version)
Mahum Naseer, Osman Hasan, Muhammad Shafique
Owing to their remarkable learning capabilities and performance in real-world applications, the use of machine learning systems based on Neural Networks (NNs) has been continuously…
Poster: Link between Bias, Node Sensitivity and Long-Tail Distribution in trained DNNs
Mahum Naseer, Muhammad Shafique
Owing to their remarkable learning (and relearning) capabilities, deep neural networks (DNNs) find use in numerous real-world applications. However, the learning of these data-driv…
UnbiasedNets: A Dataset Diversification Framework for Robustness Bias Alleviation in Neural Networks
Mahum Naseer, Bharath Srinivas Prabakaran, Osman Hasan +1
Performance of trained neural network (NN) models, in terms of testing accuracy, has improved remarkably over the past several years, especially with the advent of deep learning. H…
ISLE: A Framework for Image Level Semantic Segmentation Ensemble
Erik Ostrowski, Muhammad Shafique
One key bottleneck of employing state-of-the-art semantic segmentation networks in the real world is the availability of training labels. Conventional semantic segmentation network…
ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images
Bharath Srinivas Prabakaran, Erik Ostrowski, Muhammad Shafique
Weakly Supervised Semantic Segmentation (WSSS) relying only on image-level supervision is a promising approach to deal with the need for Segmentation networks, especially for gener…
TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents
Rachmad Vidya Wicaksana Putra, Muhammad Shafique
Autonomous mobile agents require low-power/energy-efficient machine learning (ML) algorithms to complete their ML-based tasks while adapting to diverse environments, as mobile agen…
AdvART: Adversarial Art for Camouflaged Object Detection Attacks
Amira Guesmi, Ioan Marius Bilasco, Muhammad Shafique +1
Physical adversarial attacks pose a significant practical threat as it deceives deep learning systems operating in the real world by producing prominent and maliciously designed ph…