The arrival of autonomous vehicles (AVs) promises many great benefits, including increased
safety and reduced energy consumption, pollution, and congestion. However, these engines …

Falsification detection is a critical advance in ensuring that real-time information about
vehicles and their movement states is certified on the Internet of Vehicles (IoV). Thus …

Increasingly in recent times, the mere prediction of a machine learning algorithm is
considered insufficient to gain complete control over the event being predicted. A machine …

Machine learning (ML) algorithms are nowadays widely adopted in different contexts to
perform autonomous decisions and predictions. Due to the high volume of data shared in …

Safety engineering and artificial intelligence are two fields that still need investigation on
their reciprocal interactions. Safety should be guaranteed when autonomous decision may …

Artificial intelligence and cyber-physical systems (CPS) are two of the key technologies of
the future that are enabling major global shifts. However, most of the current …

In the era of Industry 4.0, the use of Artificial Intelligence (AI) is widespread in occupational
settings. Since dealing with human safety, explainability and trustworthiness of AI are even …

Out-of-distribution detection is one of the most critical issue in the deployment of machine
learning. The data analyst must assure that data in operation should be compliant with the …

Out-of-distribution detection has become an important theme in machine learning (ML) field,
since the recognition of unseen data either “similar” or not (in-or out-of-distribution) to the …

Data augmentation is a widespread innovative technique in Artificial Intelligence: it aims at
creating new synthetic data given an existing real baseline, thus allowing to overcome the …