1 citations · 1 across the 3 of their papers we have counts for
3 papers
DILLEMA: Diffusion and Large Language Models for Multi-Modal Augmentation
Luciano Baresi, Davide Yi Xian Hu, Muhammad Irfan Mas'udi +1
Ensuring the robustness of deep learning models requires comprehensive and diverse testing. Existing approaches, often based on simple data augmentation techniques or generative ad…
Efficient Domain Augmentation for Autonomous Driving Testing Using Diffusion Models
Luciano Baresi, Davide Yi Xian Hu, Andrea Stocco +1
Simulation-based testing is widely used to assess the reliability of Autonomous Driving Systems (ADS), but its effectiveness is limited by the operational design domain (ODD) condi…
NEPTUNE: Network- and GPU-aware Management of Serverless Functions at the Edge
Luciano Baresi, Davide Yi Xian Hu, Giovanni Quattrocchi +1
Nowadays a wide range of applications is constrained by low-latency requirements that cloud infrastructures cannot meet. Multi-access Edge Computing (MEC) has been proposed as the…