Muhammad Shafique

research

∙ 08/10/2023

A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks

Machine learning (ML) is widely used today, especially through deep neur...

0 Farzad Nikfam, et al. ∙

research

∙ 08/06/2023

SAAM: Stealthy Adversarial Attack on Monoculor Depth Estimation

In this paper, we investigate the vulnerability of MDE to adversarial pa...

0 Amira Guesmi, et al. ∙

research

∙ 07/20/2023

Approximate Computing Survey, Part II: Application-Specific Architectural Approximation Techniques and Applications

The challenging deployment of compute-intensive applications from domain...

0 Vasileios Leon, et al. ∙

research

∙ 07/20/2023

Approximate Computing Survey, Part I: Terminology and Software Hardware Approximation Techniques

The rapid growth of demanding applications in domains applying multimedi...

0 Vasileios Leon, et al. ∙

research

∙ 06/29/2023

Scaling Model Checking for DNN Analysis via State-Space Reduction and Input Segmentation (Extended Version)

Owing to their remarkable learning capabilities and performance in real-...

0 Mahum Naseer, et al. ∙

research

∙ 06/15/2023

X-Rel: Energy-Efficient and Low-Overhead Approximate Reliability Framework for Error-Tolerant Applications Deployed in Critical Systems

Triple Modular Redundancy (TMR) is one of the most common techniques in ...

0 Jafar Vafaei, et al. ∙

research

∙ 06/15/2023

An Energy-Efficient Generic Accuracy Configurable Multiplier Based on Block-Level Voltage Overscaling

Voltage Overscaling (VOS) is one of the well-known techniques to increas...

0 Ali Akbar Bahoo, et al. ∙

research

∙ 05/21/2023

Reduce: A Framework for Reducing the Overheads of Fault-Aware Retraining

Fault-aware retraining has emerged as a prominent technique for mitigati...

0 Muhammad Abdullah Hanif, et al. ∙

research

∙ 05/21/2023

FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization

Permanent faults induced due to imperfections in the manufacturing proce...

0 Muhammad Abdullah Hanif, et al. ∙

research

∙ 05/19/2023

DAP: A Dynamic Adversarial Patch for Evading Person Detectors

In this paper, we present a novel approach for generating naturalistic a...

0 Amira Guesmi, et al. ∙

research

∙ 04/20/2023

eFAT: Improving the Effectiveness of Fault-Aware Training for Mitigating Permanent Faults in DNN Hardware Accelerators

Fault-Aware Training (FAT) has emerged as a highly effective technique f...

0 Muhammad Abdullah Hanif, et al. ∙

research

∙ 04/08/2023

RescueSNN: Enabling Reliable Executions on Spiking Neural Network Accelerators under Permanent Faults

To maximize the performance and energy efficiency of Spiking Neural Netw...

0 Rachmad Vidya Wicaksana Putra, et al. ∙

research

∙ 04/08/2023

EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems

Spiking Neural Networks (SNNs) have shown capabilities of achieving high...

0 Rachmad Vidya Wicaksana Putra, et al. ∙

research

∙ 04/08/2023

SwiftTron: An Efficient Hardware Accelerator for Quantized Transformers

Transformers' compute-intensive operations pose enormous challenges for ...

0 Alberto Marchisio, et al. ∙

research

∙ 04/08/2023

RobCaps: Evaluating the Robustness of Capsule Networks against Affine Transformations and Adversarial Attacks

Capsule Networks (CapsNets) are able to hierarchically preserve the pose...

0 Alberto Marchisio, et al. ∙

research

∙ 04/05/2023

FPGA-Patch: Mitigating Remote Side-Channel Attacks on FPGAs using Dynamic Patch Generation

We propose FPGA-Patch, the first-of-its-kind defense that leverages auto...

0 Mahya Morid Ahmadi, et al. ∙

research

∙ 03/29/2023

Poster: Link between Bias, Node Sensitivity and Long-Tail Distribution in trained DNNs

Owing to their remarkable learning (and relearning) capabilities, deep n...

0 Mahum Naseer, et al. ∙

research

∙ 03/24/2023

PoisonedGNN: Backdoor Attack on Graph Neural Networks-based Hardware Security Systems

Graph neural networks (GNNs) have shown great success in detecting intel...

0 Lilas Alrahis, et al. ∙

research

∙ 03/24/2023

Physical Backdoor Trigger Activation of Autonomous Vehicle using Reachability Analysis

Recent studies reveal that Autonomous Vehicles (AVs) can be manipulated ...

0 Wenqing Li, et al. ∙

research

∙ 03/14/2023

ISimDL: Importance Sampling-Driven Acceleration of Fault Injection Simulations for Evaluating the Robustness of Deep Learning

Deep Learning (DL) systems have proliferated in many applications, requi...

0 Alessio Colucci, et al. ∙

research

∙ 03/14/2023

AutoEnsemble: Automated Ensemble Search Framework for Semantic Segmentation Using Image Labels

A key bottleneck of employing state-of-the-art semantic segmentation net...

0 Erik Ostrowski, et al. ∙

research

∙ 03/14/2023

Exploring Weakly Supervised Semantic Segmentation Ensembles for Medical Imaging Systems

Reliable classification and detection of certain medical conditions, in ...

0 Erik Ostrowski, et al. ∙

research

∙ 03/14/2023

Image Label based Semantic Segmentation Framework using Object Perimeters

Achieving high-quality semantic segmentation predictions using only imag...

0 Erik Ostrowski, et al. ∙

research

∙ 03/14/2023

BoundaryCAM: A Boundary-based Refinement Framework for Weakly Supervised Semantic Segmentation of Medical Images

Weakly Supervised Semantic Segmentation (WSSS) with only image-level sup...

0 Bharath Srinivas Prabakaran, et al. ∙

research

∙ 03/14/2023

FPUS23: An Ultrasound Fetus Phantom Dataset with Deep Neural Network Evaluations for Fetus Orientations, Fetal Planes, and Anatomical Features

Ultrasound imaging is one of the most prominent technologies to evaluate...

0 Bharath Srinivas Prabakaran, et al. ∙

research

∙ 03/12/2023

DNN-Alias: Deep Neural Network Protection Against Side-Channel Attacks via Layer Balancing

Extracting the architecture of layers of a given deep neural network (DN...

0 Mahya Morid Ahmadi, et al. ∙

research

∙ 03/11/2023

SHIELD: An Adaptive and Lightweight Defense against the Remote Power Side-Channel Attacks on Multi-tenant FPGAs

Dynamic partial reconfiguration enables multi-tenancy in cloud-based FPG...

0 Mahya Morid Ahmadi, et al. ∙

research

∙ 03/08/2023

autoXFPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems

Generation and exploration of approximate circuits and accelerators has ...

0 Bharath Srinivas Prabakaran, et al. ∙

research

∙ 03/07/2023

CAE-CNNLoc: An Edge-based WiFi Fingerprinting Indoor Localization Using Convolutional Neural Network and Convolutional Auto-Encoder

With the ongoing development of Indoor Location-Based Services, accurate...

0 Amin Kargar-Barzi, et al. ∙

research

∙ 03/04/2023

scaleTRIM: Scalable TRuncation-Based Integer Approximate Multiplier with Linearization and Compensation

Approximate computing (AC) has become a prominent solution to improve th...

0 Ebrahim Farahmand, et al. ∙

research

∙ 03/03/2023

TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents

Autonomous mobile agents require low-power/energy-efficient machine lear...

0 Rachmad Vidya Wicaksana Putra, et al. ∙

research

∙ 03/03/2023

Exploring Machine Learning Privacy/Utility trade-off from a hyperparameters Lens

Machine Learning (ML) architectures have been applied to several applica...

0 Ayoub Arous, et al. ∙

research

∙ 03/03/2023

AdvART: Adversarial Art for Camouflaged Object Detection Attacks

A majority of existing physical attacks in the real world result in cons...

4 Amira Guesmi, et al. ∙

research

∙ 03/02/2023

APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation

In recent years, monocular depth estimation (MDE) has witnessed a substa...

11 Amira Guesmi, et al. ∙

research

∙ 03/02/2023

AdvRain: Adversarial Raindrops to Attack Camera-based Smart Vision Systems

Vision-based perception modules are increasingly deployed in many applic...

0 Amira Guesmi, et al. ∙

research

∙ 02/24/2023

UnbiasedNets: A Dataset Diversification Framework for Robustness Bias Alleviation in Neural Networks

Performance of trained neural network (NN) models, in terms of testing a...

0 Mahum Naseer, et al. ∙

research

∙ 12/24/2022

Mantis: Enabling Energy-Efficient Autonomous Mobile Agents with Spiking Neural Networks

Autonomous mobile agents such as unmanned aerial vehicles (UAVs) and mob...

0 Rachmad Vidya Wicaksana Putra, et al. ∙

research

∙ 12/20/2022

ATLAS: An IoT Architecture and Secure Open-source Networking Stack for Anonymous Localization and Tracking Using Smartphones and Bluetooth Beacons

Bluetooth (BT) has revolutionized close-range communication enabling sma...

0 Bharath Srinivas Prabakaran, et al. ∙

research

∙ 11/29/2022

Building Resilience to Out-of-Distribution Visual Data via Input Optimization and Model Finetuning

A major challenge in machine learning is resilience to out-of-distributi...

0 Christopher J. Holder, et al. ∙

research

∙ 11/09/2022

Efficient Neural Mapping for Localisation of Unmanned Ground Vehicles

Global localisation from visual data is a challenging problem applicable...

0 Christopher J. Holder, et al. ∙

research

∙ 10/13/2022

AccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient

Adversarial training is exploited to develop a robust Deep Neural Networ...

0 Farzad Nikfam, et al. ∙

research

∙ 10/11/2022

RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks

Neural Architecture Search (NAS) algorithms aim at finding efficient Dee...

0 Alberto Marchisio, et al. ∙

research

∙ 08/17/2022

Embracing Graph Neural Networks for Hardware Security (Invited Paper)

Graph neural networks (GNNs) have attracted increasing attention due to ...

0 Lilas Alrahis, et al. ∙

research

∙ 08/03/2022

LaneSNNs: Spiking Neural Networks for Lane Detection on the Loihi Neuromorphic Processor

Autonomous Driving (AD) related features represent important elements fo...

0 Alberto Viale, et al. ∙

research

∙ 07/31/2022

CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks

In today's era of smart cyber-physical systems, Deep Neural Networks (DN...

0 Muhammad Abdullah Hanif, et al. ∙

research

∙ 07/31/2022

enpheeph: A Fault Injection Framework for Spiking and Compressed Deep Neural Networks

Research on Deep Neural Networks (DNNs) has focused on improving perform...

0 Alessio Colucci, et al. ∙

research

∙ 06/21/2022

Enabling Capsule Networks at the Edge through Approximate Softmax and Squash Operations

Complex Deep Neural Networks such as Capsule Networks (CapsNets) exhibit...

0 Alberto Marchisio, et al. ∙

research

∙ 06/17/2022

tinySNN: Towards Memory- and Energy-Efficient Spiking Neural Networks

Larger Spiking Neural Network (SNN) models are typically favorable as th...

0 Rachmad Vidya Wicaksana Putra, et al. ∙

research

∙ 06/17/2022

On Efficient Real-Time Semantic Segmentation: A Survey

Semantic segmentation is the problem of assigning a class label to every...

0 Christopher J. Holder, et al. ∙

research

∙ 06/01/2022

NeuroUnlock: Unlocking the Architecture of Obfuscated Deep Neural Networks

The advancements of deep neural networks (DNNs) have led to their deploy...

0 Mahya Morid Ahmadi, et al. ∙

Muhammad Shafique

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