154 citations · 780 across the 51 of their papers we have counts for
11 papers · 1 filter
GenAI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusions
Mirko Casu, Luca Guarnera, Pasquale Caponnetto +1
This paper examines the impact of cognitive biases on decision-making in forensics and digital forensics, exploring biases such as confirmation bias, anchoring bias, and hindsight…
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…
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…
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…
Innovative Methods for Non-Destructive Inspection of Handwritten Documents
Eleonora Breci, Luca Guarnera, Sebastiano Battiato
Handwritten document analysis is an area of forensic science, with the goal of establishing authorship of documents through examination of inherent characteristics. Law enforcement…
Improving Video Deepfake Detection: A DCT-Based Approach with Patch-Level Analysis
Luca Guarnera, Salvatore Manganello, Sebastiano Battiato
A new algorithm for the detection of deepfakes in digital videos is presented. The I-frames were extracted in order to provide faster computation and analysis than approaches descr…
Not with my name! Inferring artists' names of input strings employed by Diffusion Models
Roberto Leotta, Oliver Giudice, Luca Guarnera +1
Diffusion Models (DM) are highly effective at generating realistic, high-quality images. However, these models lack creativity and merely compose outputs based on their training da…
Boosting multiple sclerosis lesion segmentation through attention mechanism
Alessia Rondinella, Elena Crispino, Francesco Guarnera +7
Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression. Although several attempts have been made to segment mult…
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…
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…
Level Up the Deepfake Detection: a Method to Effectively Discriminate Images Generated by GAN Architectures and Diffusion Models
Luca Guarnera, Oliver Giudice, Sebastiano Battiato
The image deepfake detection task has been greatly addressed by the scientific community to discriminate real images from those generated by Artificial Intelligence (AI) models: a…