5 citations · 12 across the 7 of their papers we have counts for
19 papers
Fault-Aware Design and Training to Enhance DNNs Reliability with Zero-Overhead
Niccolò Cavagnero, Fernando Dos Santos, Marco Ciccone +3
Deep Neural Networks (DNNs) enable a wide series of technological advancements, ranging from clinical imaging, to predictive industrial maintenance and autonomous driving. However,…
Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation
Silvia Bucci, Francesco Cappio Borlino, Barbara Caputo +1
Vision systems trained in closed-world scenarios fail when presented with new environmental conditions, new data distributions, and novel classes at deployment time. How to move to…
Towards Fairness Certification in Artificial Intelligence
Tatiana Tommasi, Silvia Bucci, Barbara Caputo +1
Thanks to the great progress of machine learning in the last years, several Artificial Intelligence (AI) techniques have been increasingly moving from the controlled research labor…
Denoise and Contrast for Category Agnostic Shape Completion
Antonio Alliegro, Diego Valsesia, Giulia Fracastoro +2
In this paper, we present a deep learning model that exploits the power of self-supervision to perform 3D point cloud completion, estimating the missing part and a context region a…
Multi-Modal RGB-D Scene Recognition Across Domains
Andrea Ferreri, Silvia Bucci, Tatiana Tommasi
Scene recognition is one of the basic problems in computer vision research with extensive applications in robotics. When available, depth images provide helpful geometric cues that…
Rethinking Domain Generalization Baselines
Francesco Cappio Borlino, Antonio D'Innocente, Tatiana Tommasi
Despite being very powerful in standard learning settings, deep learning models can be extremely brittle when deployed in scenarios different from those on which they were trained.…