1 citations · 1 across the 3 of their papers we have counts for
3 papers
eess.IV2023
Learning-Based and Quality Preserving Super-Resolution of Noisy Images
Simone Cammarasana, Giuseppe Patanè
Several applications require the super-resolution of noisy images and the preservation of geometrical and texture features. State-of-the-art super-resolution methods do not account…
cs.DM2023★ 1 cited
Graph-Based Analysis and Visualisation of Mobility Data
Rafael Martínez Márquez, Giuseppe Patanè
Urban mobility forecast and analysis can be addressed through grid-based and graph-based models. However, graph-based representations have the advantage of more realistically depic…
cs.CV2023
Learning-based Framework for US Signals Super-resolution
Simone Cammarasana, Paolo Nicolardi, Giuseppe Patanè
We propose a novel deep-learning framework for super-resolution ultrasound images and videos in terms of spatial resolution and line reconstruction. We up-sample the acquired low-r…