986 citations · 1.1k across the 57 of their papers we have counts for
16 papers · 1 filter
Wake-Sleep Consolidated Learning
Amelia Sorrenti, Giovanni Bellitto, Federica Proietto Salanitri +3
We propose Wake-Sleep Consolidated Learning (WSCL), a learning strategy leveraging Complementary Learning System theory and the wake-sleep phases of the human brain to improve the…
Radiomics Boosts Deep Learning Model for IPMN Classification
Lanhong Yao, Zheyuan Zhang, Ugur Demir +14
Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their ri…
Domain Generalization with Fourier Transform and Soft Thresholding
Hongyi Pan, Bin Wang, Zheyuan Zhang +5
Domain generalization aims to train models on multiple source domains so that they can generalize well to unseen target domains. Among many domain generalization methods, Fourier-t…
MatFuse: Controllable Material Generation with Diffusion Models
Giuseppe Vecchio, Renato Sortino, Simone Palazzo +1
Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a uni…
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…
A Privacy-Preserving Walk in the Latent Space of Generative Models for Medical Applications
Matteo Pennisi, Federica Proietto Salanitri, Giovanni Bellitto +3
Generative Adversarial Networks (GANs) have demonstrated their ability to generate synthetic samples that match a target distribution. However, from a privacy perspective, using GA…
RADiff: Controllable Diffusion Models for Radio Astronomical Maps Generation
Renato Sortino, Thomas Cecconello, Andrea DeMarco +10
Along with the nearing completion of the Square Kilometre Array (SKA), comes an increasing demand for accurate and reliable automated solutions to extract valuable information from…
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…
On the Effectiveness of Equivariant Regularization for Robust Online Continual Learning
Lorenzo Bonicelli, Matteo Boschini, Emanuele Frascaroli +6
Humans can learn incrementally, whereas neural networks forget previously acquired information catastrophically. Continual Learning (CL) approaches seek to bridge this gap by facil…
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…
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…
Radio astronomical images object detection and segmentation: A benchmark on deep learning methods
Renato Sortino, Daniel Magro, Giuseppe Fiameni +9
In recent years, deep learning has been successfully applied in various scientific domains. Following these promising results and performances, it has recently also started being e…
TinyHD: Efficient Video Saliency Prediction with Heterogeneous Decoders using Hierarchical Maps Distillation
Feiyan Hu, Simone Palazzo, Federica Proietto Salanitri +4
Video saliency prediction has recently attracted attention of the research community, as it is an upstream task for several practical applications. However, current solutions are p…