activity
20192026
most citedDeep-PowerX: A Deep Learning-Based Framework for Low-Power Approximate Logic Synthesis

17 citations · 35 across the 29 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

FAIR-SIGHT: Fairness Assurance in Image Recognition via Simultaneous Conformal Thresholding and Dynamic Output Repair

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

We introduce FAIR-SIGHT, an innovative post-hoc framework designed to ensure fairness in computer vision systems by combining conformal prediction with a dynamic output repair mech…

cs.CV2022

A Fast and Efficient Conditional Learning for Tunable Trade-Off between Accuracy and Robustness

Souvik Kundu, Sairam Sundaresan, Massoud Pedram +1

Existing models that achieve state-of-the-art (SOTA) performance on both clean and adversarially-perturbed images rely on convolution operations conditioned with feature-wise linea…

cs.CV20203 cited

A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs

Souvik Kundu, Mahdi Nazemi, Peter A. Beerel +1

This paper presents a dynamic network rewiring (DNR) method to generate pruned deep neural network (DNN) models that are robust against adversarial attacks yet maintain high accura…

cs.CV2020

Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space

Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen +3

Recent advances in the field of artificial intelligence have been made possible by deep neural networks. In applications where data are scarce, transfer learning and data augmentat…

cs.CV2020

Pre-defined Sparsity for Low-Complexity Convolutional Neural Networks

Souvik Kundu, Mahdi Nazemi, Massoud Pedram +2

The high energy cost of processing deep convolutional neural networks impedes their ubiquitous deployment in energy-constrained platforms such as embedded systems and IoT devices.…