1 citations · 1 across the 4 of their papers we have counts for
4 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…