activity
20192022
most citedSceneAdapt: Scene-based domain adaptation for semantic segmentation using adversarial learning

20 citations · 23 across the 4 of their papers we have counts for

collaborators

7 papers

math.NA20222 cited

Evaluating Accuracy and Efficiency of HPC Solvers for Sparse Linear Systems with Applications to PDEs

Antonella Galizia, Simone Cammarasana, Andrea Clematis +1

Partial Differential Equations (PDEs) describe several problems relevant to many fields of applied sciences, and their discrete counterparts typically involve the solution of spars…

math.NA2021

VEM and the Mesh

Tommaso Sorgente, Daniele Prada, Daniela Cabiddu +6

In this work we report some results, obtained within the framework of the ERC Project CHANGE, on the impact on the performance of the virtual element method of the shape of the pol…

cs.LG20201 cited

Fourier-based and Rational Graph Filters for Spectral Processing

Giuseppe Patanè

Data are represented as graphs in a wide range of applications, such as Computer Vision (e.g., images) and Graphics (e.g., 3D meshes), network analysis (e.g., social networks), and…

cs.GR2020

Meshless Approximation and Helmholtz-Hodge Decomposition of Vector Fields

Giuseppe Patanè

The analysis of vector fields is crucial for the understanding of several physical phenomena, such as natural events (e.g., analysis of waves), diffusive processes, electric and el…

math.OC2020

Continuous Fuzzy Transform as Integral Operator

Giuseppe Patanè

The Fuzzy transform is ubiquitous in different research fields and applications, such as image and data compression, data mining, knowledge discovery, and the analysis of linguisti…

cs.CV202020 cited

SceneAdapt: Scene-based domain adaptation for semantic segmentation using adversarial learning

Daniele Di Mauro, Antonino Furnari, Giuseppe Patanè +2

Semantic segmentation methods have achieved outstanding performance thanks to deep learning. Nevertheless, when such algorithms are deployed to new contexts not seen during trainin…