8 citations · 21 across the 17 of their papers we have counts for
17 papers
The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection
Riccardo Raciti, Francesco Guarnera, Francesco Rundo +2
In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while beneficial for privacy-preserving da…
AIM 2024 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Dmitry Vatolin +30
This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provid…
SalFoM: Dynamic Saliency Prediction with Video Foundation Models
Morteza Moradi, Mohammad Moradi, Francesco Rundo +3
Recent advancements in video saliency prediction (VSP) have shown promising performance compared to the human visual system, whose emulation is the primary goal of VSP. However, cu…
Deep Learning Algorithm for Advanced Level-3 Inverse-Modeling of Silicon-Carbide Power MOSFET Devices
Massimo Orazio Spata, Sebastiano Battiato, Alessandro Ortis +4
Inverse modelling with deep learning algorithms involves training deep architecture to predict device's parameters from its static behaviour. Inverse device modelling is suitable t…
Car-Driver Drowsiness Assessment through 1D Temporal Convolutional Networks
Francesco Rundo, Concetto Spampinato, Michael Rundo
Recently, the scientific progress of Advanced Driver Assistance System solutions (ADAS) has played a key role in enhancing the overall safety of driving. ADAS technology enables ac…
Visual Saliency Detection in Advanced Driver Assistance Systems
Francesco Rundo, Michael Sebastian Rundo, Concetto Spampinato
Visual Saliency refers to the innate human mechanism of focusing on and extracting important features from the observed environment. Recently, there has been a notable surge of int…
Non-Linear Self Augmentation Deep Pipeline for Cancer Treatment outcome Prediction
Francesco Rundo, Concetto Spampinato, Michael Rundo
Immunotherapy emerges as promising approach for treating cancer. Encouraging findings have validated the efficacy of immunotherapy medications in addressing tumors, resulting in pr…
MeT: A Graph Transformer for Semantic Segmentation of 3D Meshes
Giuseppe Vecchio, Luca Prezzavento, Carmelo Pino +3
Polygonal meshes have become the standard for discretely approximating 3D shapes, thanks to their efficiency and high flexibility in capturing non-uniform shapes. This non-uniformi…
BioTrak: A Blockchain-based Platform for Food Chain Logistics Traceability
A. Spitalleri, I. Kavasidis, V. Cartelli +5
The food supply chain, following its globalization, has become very complex. Such complexities, introduce factors that influence adversely the quality of intermediate and final pro…
A baseline on continual learning methods for video action recognition
Giulia Castagnolo, Concetto Spampinato, Francesco Rundo +2
Continual learning has recently attracted attention from the research community, as it aims to solve long-standing limitations of classic supervisedly-trained models. However, most…
Early detection of hip periprosthetic joint infections through CNN on Computed Tomography images
Francesco Guarnera, Alessia Rondinella, Oliver Giudice +6
Early detection of an infection prior to prosthesis removal (e.g., hips, knees or other areas) would provide significant benefits to patients. Currently, the detection task is carr…
Deep Learning Systems for Advanced Driving Assistance
Francesco Rundo
Next generation cars embed intelligent assessment of car driving safety through innovative solutions often based on usage of artificial intelligence. The safety driving monitoring…
UniCT DMI Solution for 3rd COV19D Competition on COVID-19 Detection through attention-based CNN for CT Scan
Alessia Rondinella, Francesco Guarnera, Oliver Giudice +3
This paper presents our solution for the first challenge of the 3rd Covid-19 competition, which is part of the "AI-enabled Medical Image Analysis Workshop" organized by IEEE Intern…
Transformer-based Image Generation from Scene Graphs
Renato Sortino, Simone Palazzo, Concetto Spampinato
Graph-structured scene descriptions can be efficiently used in generative models to control the composition of the generated image. Previous approaches are based on the combination…
An Explainable AI System for Automated COVID-19 Assessment and Lesion Categorization from CT-scans
Matteo Pennisi, Isaak Kavasidis, Concetto Spampinato +12
COVID-19 infection caused by SARS-CoV-2 pathogen is a catastrophic pandemic outbreak all over the world with exponential increasing of confirmed cases and, unfortunately, deaths. I…
Hierarchical Domain-Adapted Feature Learning for Video Saliency Prediction
Giovanni Bellitto, Federica Proietto Salanitri, Simone Palazzo +3
In this work, we propose a 3D fully convolutional architecture for video saliency prediction that employs hierarchical supervision on intermediate maps (referred to as conspicuity…
Domain Adaptation for Outdoor Robot Traversability Estimation from RGB data with Safety-Preserving Loss
Simone Palazzo, Dario C. Guastella, Luciano Cantelli +5
Being able to estimate the traversability of the area surrounding a mobile robot is a fundamental task in the design of a navigation algorithm. However, the task is often complex,…