activity
20222024
most citedLevel Up the Deepfake Detection: a Method to Effectively Discriminate Images Generated by GAN Architectures and Diffusion Models

4 citations · 11 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2024

Uncertainty-guided Open-Set Source-Free Unsupervised Domain Adaptation with Target-private Class Segregation

Mattia Litrico, Davide Talon, Sebastiano Battiato +3

Standard Unsupervised Domain Adaptation (UDA) aims to transfer knowledge from a labeled source domain to an unlabeled target but usually requires simultaneous access to both source…

cs.CV20241 cited

On the exploitation of DCT statistics for cropping detectors

Claudio Vittorio Ragaglia, Francesco Guarnera, Sebastiano Battiato

{The study of frequency components derived from Discrete Cosine Transform (DCT) has been widely used in image analysis. In recent years it has been observed that significant inform…

cs.CV2024

A Novel Dataset for Non-Destructive Inspection of Handwritten Documents

Eleonora Breci, Luca Guarnera, Sebastiano Battiato

Forensic handwriting examination is a branch of Forensic Science that aims to examine handwritten documents in order to properly define or hypothesize the manuscript's author. Thes…

cs.DL2023

An Innovative Tool for Uploading/Scraping Large Image Datasets on Social Networks

Nicolò Fabio Arceri, Oliver Giudice, Sebastiano Battiato

Nowadays, people can retrieve and share digital information in an increasingly easy and fast fashion through the well-known digital platforms, including sensitive data, inappropria…

cs.SD2023

Deep Audio Analyzer: a Framework to Industrialize the Research on Audio Forensics

Valerio Francesco Puglisi, Oliver Giudice, Sebastiano Battiato

Deep Audio Analyzer is an open source speech framework that aims to simplify the research and the development process of neural speech processing pipelines, allowing users to conce…

eess.SP20233 cited

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…