Abstract Context Machine Learning (ML) has been at the heart of many innovations over the
past years. However, including it in so-called “safety-critical” systems such as automotive or …

The rapid development of Machine Learning (ML) has demonstrated superior performance
in many areas, such as computer vision and video and speech recognition. It has now been …

The wide deployment of Deep Neural Networks (DNN) in high-performance cloud
computing platforms brought to light multi-tenant cloud field-programmable gate arrays …

Recent advances in neural networks (NNs) and their applications in deep learning
techniques have made the security aspects of NNs an important and timely topic for …

Deep neural networks (DNNs) have become one of the enabling technologies in many
safety-critical applications, eg, autonomous driving and medical image analysis. DNN …

The advent of High-Performance Computing has led to the adoption of Convolutional Neural
Networks (CNNs) in safety-critical applications such as autonomous vehicles. However …

Hardware security is currently a very influential domain, where each year countless works
are published concerning attacks against hardware and countermeasures. A significant …

Deep neural network (deepnet) applications play a crucial role in safety-critical systems
such as autonomous vehicles (AVs). An AV must drive safely towards its destination …

DNNs have become pervasive in many security–critical scenarios such as autonomous
vehicles and medical diagnoses. Recent studies reveal the susceptibility of DNNs to various …

On-orbit object detection has received extensive attention in the field of artificial intelligence
(AI) in space research. Deep-learning-based object-detection algorithms are often …