2 citations · 4 across the 7 of their papers we have counts for
7 papers
Special Session: Approximation and Fault Resiliency of DNN Accelerators
Mohammad Hasan Ahmadilivani, Mario Barbareschi, Salvatore Barone +9
Deep Learning, and in particular, Deep Neural Network (DNN) is nowadays widely used in many scenarios, including safety-critical applications such as autonomous driving. In this co…
APPRAISER: DNN Fault Resilience Analysis Employing Approximation Errors
Mahdi Taheri, Mohammad Hasan Ahmadilivani, Maksim Jenihhin +2
Nowadays, the extensive exploitation of Deep Neural Networks (DNNs) in safety-critical applications raises new reliability concerns. In practice, methods for fault injection by emu…
A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks
Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik +2
Artificial Intelligence (AI) and, in particular, Machine Learning (ML) have emerged to be utilized in various applications due to their capability to learn how to solve complex pro…
DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators
Mahdi Taheri, Mohammad Riazati, Mohammad Hasan Ahmadilivani +5
While the role of Deep Neural Networks (DNNs) in a wide range of safety-critical applications is expanding, emerging DNNs experience massive growth in terms of computation power. I…
Hybrid Protection of Digital FIR Filters
Levent Aksoy, Quang-Linh Nguyen, Felipe Almeida +4
A digital Finite Impulse Response (FIR) filter is a ubiquitous block in digital signal processing applications and its behavior is determined by its coefficients. To protect filter…
Survey on Architectural Attacks: A Unified Classification and Attack Model
Tara Ghasempouri, Jaan Raik, Cezar Reinbrecht +2
According to the World Economic Forum, cyber attacks are considered as one of the most important sources of risk to companies and institutions worldwide. Attacks can target the net…