Deep learning tasks cover a broad range of domains and an even more extensive range of
applications, from entertainment to extremely safety-critical fields. Thus, Deep Neural …

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 …

Convolutional Neural Networks (CNNs) are being increasingly used in safety-critical and
high-performance computing systems. As such systems require high levels of resilience to …

Guaranteeing safety is always a prerequisite in the process of realizing various automotive
applications. However, the automotive functional safety design has been challenged by …

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 …

This article presents a novel approach to designing and validating a fully electronic braking
pedal, addressing the growing integration of electronics in vehicles. With the imminent rise …

Modular multilevel converters are well known in the energy sector. Generally, their stable
operation is at the expense of numerous sensors, communication burden, and …

This paper proposes a novel method for a structural test of the Successive Approximate
Register (SAR) Analog to Digital Converter (ADC). The presented strategy has an ignorable …

Over the last few decades, automotive embedded Information and Communication
Technology (ICT) systems have been used to enhance vehicle performance and enrich …

As the automotive industry marches towards higher level of autonomous driving, the design
supply chain is shaping up to support a great level of complexity and new requirements …