activity
20182021
most citedBioNetExplorer: Architecture-Space Exploration of Bio-Signal Processing Deep Neural Networks for Wearables

21 citations · 47 across the 3 of their papers we have counts for

collaborators

13 papers

eess.SP202121 cited

BioNetExplorer: Architecture-Space Exploration of Bio-Signal Processing Deep Neural Networks for Wearables

Bharath Srinivas Prabakaran, Asima Akhtar, Semeen Rehman +2

In this work, we propose the BioNetExplorer framework to systematically generate and explore multiple DNN architectures for bio-signal processing in wearables. Our framework adapts…

cs.LG2020

MLComp: A Methodology for Machine Learning-based Performance Estimation and Adaptive Selection of Pareto-Optimal Compiler Optimization Sequences

Alessio Colucci, Dávid Juhász, Martin Mosbeck +6

Embedded systems have proliferated in various consumer and industrial applications with the evolution of Cyber-Physical Systems and the Internet of Things. These systems are subjec…

eess.SP201913 cited

XBioSiP: A Methodology for Approximate Bio-Signal Processing at the Edge

Bharath Srinivas Prabakaran, Semeen Rehman, Muhammad Shafique

Bio-signals exhibit high redundancy, and the algorithms for their processing are inherently error resilient. This property can be leveraged to improve the energy-efficiency of IoT-…

cs.CR201913 cited

RED-Attack: Resource Efficient Decision based Attack for Machine Learning

Faiq Khalid, Hassan Ali, Muhammad Abdullah Hanif +3

Due to data dependency and model leakage properties, Deep Neural Networks (DNNs) exhibit several security vulnerabilities. Several security attacks exploited them but most of them…

cs.CR2018

ForASec: Formal Analysis of Security Vulnerabilities in Sequential Circuits

Faiq Khalid, Imran Hafeez Abbassi, Semeen Rehman +3

Security vulnerability analysis of Integrated Circuits using conventional design-time validation and verification techniques (like simulations, emulations, etc.) is generally a com…

cs.CR2018

TrojanZero: Switching Activity-Aware Design of Undetectable Hardware Trojans with Zero Power and Area Footprint

Imran Hafeez Abbassi, Faiq Khalid, Semeen Rehman +4

Conventional Hardware Trojan (HT) detection techniques are based on the validation of integrated circuits to determine changes in their functionality, and on non-invasive side-chan…