Hardware realization of artificial intelligence (AI) requires new design styles and even
underlying technologies than those used in traditional digital processors or logic circuits …

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 …

Fault management in digital chips is a crucial aspect of functional safety. Significant work
has been done on gate and microarchitecture level triple modular redundancy, and on …

Over the years, significant work has been done on high-integrity systems, such as those
found in cars, satellites and aircrafts, to minimize the risk that a logic fault causes a system …

Deep neural networks (DNNs) in safety-critical applications demand high reliability even
when running on edge-computing devices. Recent works on System-on-Chip (SoC) design …

The occurrence of radiation-induced soft errors in electronic computing systems can either
affect non-essential system functionalities or violate safety–critical conditions, which might …

Driven by the success of machine learning algorithms for recognizing and identifying
objects, there are significant efforts to exploit convolutional neural networks (CNNs) in edge …

Deep neural network (DNN) models are being deployed in safety-critical embedded devices
for object identification, recognition, and even trajectory prediction. Optimized versions of …

This article compares and assesses the effectiveness of three prominent machine learning
(ML) models for tiny ML computing systems in tolerating neutron-induced soft errors. Results …

Abstract Machine Learning (ML) is currently being exploited in numerous applications, being
one of the most effective Artificial Intelligence (AI) technologies used in diverse fields, such …