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 …

Modern neural network complexity has grown dramatically in recent years, leading to the
adoption of hardware-accelerated solutions to cope with the computational power required …

Artificial intelligence (AI) systems are increasingly popular in many applications.
Nevertheless, AI technologies are still developing, and many issues need to be addressed …

Research on Deep Neural Networks (DNNs) has focused on improving performance and
accuracy for real-world deployments, leading to new models, such as Spiking Neural …

In an age dominated by resource-intensive foundation models the ability to efficiently adapt
to downstream tasks is crucial. Visual Prompting (VP) drawing inspiration from the prompting …

Abstract Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance
in many computer vision tasks. However high computational and storage demands hinder …

Convolutional Neural Networks (CNNs) have revolutionized many applications in recent
years, especially in image classification, video processing, and pattern recognition. This …

Incorporating resilience in design is important for the long-term viability of complex
engineered systems. Complex aerospace systems, for example, must ensure safety in the …

The rapid advancement of Artificial Intelligence (AI) has led to its integration into various
areas, especially with Large Language Models (LLMs) significantly enhancing capabilities …

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 …