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

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 …

This article presents a platform and design appr-oach for enabling radiation-tolerant deep
learning acceleration on static random access memory (SRAM)-based 20-nm Kintex …

Pre-trained BERT models have achieved impressive accuracy on natural language
processing (NLP) tasks. However, their excessive amount of parameters hinders them from …

With the rapid advancements of deep learning in the past decade, it can be foreseen that
deep learning will be continuously deployed in more and more safety-critical applications …

Soft errors in large VLSI circuits have a significant impact on computing-and memory-
intensive neural network (NN) processing. Understanding the influence of soft errors on NNs …

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 as …

Automotive applications with safety requirements must adhere to specific regulations such
as ISO 26262, which imposes the use of diverse redundancy for the highest integrity levels …

Convolutional Neural Networks (CNNs) have been applied in wide areas of computer vision,
and edge intelligence is expected to provide instant AI service with the support of broadband …

Convolutional neural networks (CNN) have become essential for many scientific and
industrial applications, such as image classification and pattern detection. Among the …