Search Results for author:
Found 36 papers, 8 papers with code
Uncertainty-guided Open-Set Source-Free Unsupervised Domain Adaptation with Target-private Class Segregation
We propose a novel approach for SF-OSDA that exploits the granularity of target-private categories by segregating their samples into multiple unknown classes.
On the exploitation of DCT statistics for cropping detectors
In this work, we investigated a novel image resolution classifier that employs DCT statistics with the goal to detect the original resolution of images; in particular the insight was exploited to address the challenge of identifying cropped images.
On the Exploitation of DCT-Traces in the Generative-AI Domain
Deepfakes represent one of the toughest challenges in the world of Cybersecurity and Digital Forensics, especially considering the high-quality results obtained with recent generative AI-based solutions.
MITS-GAN: Safeguarding Medical Imaging from Tampering with Generative Adversarial Networks
The progress in generative models, particularly Generative Adversarial Networks (GANs), opened new possibilities for image generation but raised concerns about potential malicious uses, especially in sensitive areas like medical imaging.
A Novel Dataset for Non-Destructive Inspection of Handwritten Documents
Preliminary results on the proposed datasets show that 90% classification accuracy can be achieved on the first subset (documents written on both paper and pen and later digitized and on tablets) and 96% on the second portion of the data.
AI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusions
This paper provides a comprehensive analysis of cognitive biases in forensics and digital forensics, examining their implications for decision-making processes in these fields.
An Innovative Tool for Uploading/Scraping Large Image Datasets on Social Networks
Nowadays, people can retrieve and share digital information in an increasingly easy and fast fashion through the well-known digital platforms, including sensitive data, inappropriate or illegal content, and, in general, information that might serve as probative evidence in court.
Innovative Methods for Non-Destructive Inspection of Handwritten Documents
Handwritten document analysis is an area of forensic science, with the goal of establishing authorship of documents through examination of inherent characteristics.
Improving Video Deepfake Detection: A DCT-Based Approach with Patch-Level Analysis
A new algorithm for the detection of deepfakes in digital videos is presented.
Deep Learning Algorithm for Advanced Level-3 Inverse-Modeling of Silicon-Carbide Power MOSFET Devices
Channel length of power MOSFET is a key parameter involved in the static and dynamic behaviour of the device.
Not with my name! Inferring artists' names of input strings employed by Diffusion Models
In this paper, a preliminary study to infer the probability of use of an artist's name in the input string of a generated image is presented.
Boosting multiple sclerosis lesion segmentation through attention mechanism
Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression.
Early detection of hip periprosthetic joint infections through CNN on Computed Tomography images
Early detection of an infection prior to prosthesis removal (e. g., hips, knees or other areas) would provide significant benefits to patients.
UniCT DMI Solution for 3rd COV19D Competition on COVID-19 Detection through attention-based CNN for CT Scan
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 International Conference on Acoustic, Speech and Signal Processing (ICASSP) 2023.
Level Up the Deepfake Detection: a Method to Effectively Discriminate Images Generated by GAN Architectures and Diffusion Models
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 binary classification task.
CNN-based first quantization estimation of double compressed JPEG images
Multiple JPEG compressions leave artifacts in digital images: residual traces that could be exploited in forensics investigations to recover information about the device employed for acquisition or image editing software.
Transfer Learning via Test-Time Neural Networks Aggregation
The proposed aggregation loss allows our model to learn how trained deep network parameters can be aggregated with an aggregation operator.
Introducing AV1 Codec-Level Video Steganography
Steganography is the ancient art of concealing messages into data.
On the Exploitation of Deepfake Model Recognition
Despite recent advances in Generative Adversarial Networks (GANs), with special focus to the Deepfake phenomenon there is no a clear understanding neither in terms of explainability nor of recognition of the involved models.
Deepfake Style Transfer Mixture: a First Forensic Ballistics Study on Synthetic Images
Most recent style-transfer techniques based on generative architectures are able to obtain synthetic multimedia contents, or commonly called deepfakes, with almost no artifacts.
A Survey on Human-aware Robot Navigation
This paper is concerned with the navigation aspect of a socially-compliant robot and provides a survey of existing solutions for the relevant areas of research as well as an outlook on possible future directions.
Fighting deepfakes by detecting GAN DCT anomalies
To properly contrast the Deepfake phenomenon the need to design new Deepfake detection algorithms arises; the misuse of this formidable A. I.
Computational data analysis for first quantization estimation on JPEG double compressed images
Multimedia Forensics experts work consists in providing answers about integrity of a specific media content and from where it comes from.
In-Depth DCT Coefficient Distribution Analysis for First Quantization Estimation
The exploitation of traces in JPEG double compressed images is of utter importance for investigations.
Fighting Deepfake by Exposing the Convolutional Traces on Images
In this paper, a new approach aimed to extract a Deepfake fingerprint from images is proposed.
Animated GIF optimization by adaptive color local table management
The proposed technique is based on Local Color Table selection and color remapping in order to create optimized animated GIFs while preserving the original format.
Pollen13K: A Large Scale Microscope Pollen Grain Image Dataset
Pollen grain classification has a remarkable role in many fields from medicine to biology and agronomy.
Single architecture and multiple task deep neural network for altered fingerprint analysis
Fingerprints are one of the most copious evidence in a crime scene and, for this reason, they are frequently used by law enforcement for identification of individuals.
SceneAdapt: Scene-based domain adaptation for semantic segmentation using adversarial learning
We formalize this problem as a domain adaptation task and introduce a novel dataset of urban scenes with the related semantic labels.
Preliminary Forensics Analysis of DeepFake Images
One of the most terrifying phenomenon nowadays is the DeepFake: the possibility to automatically replace a person's face in images and videos by exploiting algorithms based on deep learning.
Survey on Visual Sentiment Analysis
The paper also includes a description of new challenges, the evaluation from the viewpoint of progress toward more sophisticated systems and related practical applications, as well as a summary of the insights resulting from this study.
DeepFake Detection by Analyzing Convolutional Traces
The Deepfake phenomenon has become very popular nowadays thanks to the possibility to create incredibly realistic images using deep learning tools, based mainly on ad-hoc Generative Adversarial Networks (GAN).
EGO-CH: Dataset and Fundamental Tasks for Visitors BehavioralUnderstanding using Egocentric Vision
Equipping visitors of a cultural site with a wearable device allows to easily collect information about their preferences which can be exploited to improve the fruition of cultural goods with augmented reality.
Next-Active-Object prediction from Egocentric Videos
Although First Person Vision systems can sense the environment from the user's perspective, they are generally unable to predict his intentions and goals.
Egocentric Visitors Localization in Cultural Sites
We consider the problem of localizing visitors in a cultural site from egocentric (first person) images.
A Fast Palette Reordering Technique Based on GPU-Optimized Genetic Algorithms
Color re-indexing is one of main approaches for improving the loss-less compression of color indexed images.
