Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Gragnaniello, Diego"'
Publikováno v:
In Engineering Applications of Artificial Intelligence January 2025 139 Part A
The ever higher quality and wide diffusion of fake images have spawn a quest for reliable forensic tools. Many GAN image detectors have been proposed, recently. In real world scenarios, however, most of them show limited robustness and generalization
Externí odkaz:
http://arxiv.org/abs/2112.12606
Publikováno v:
In Expert Systems With Applications 1 December 2024 255 Part D
The advent of deep learning has brought a significant improvement in the quality of generated media. However, with the increased level of photorealism, synthetic media are becoming hardly distinguishable from real ones, raising serious concerns about
Externí odkaz:
http://arxiv.org/abs/2104.02617
Autor:
Gravina, Michela, Gragnaniello, Diego, Verdoliva, Luisa, Poggi, Giovanni, Corsini, Iuri, Dani, Carlo, Meneghin, Fabio, Lista, Gianluca, Aversa, Salvatore, Raimondi, Francesco, Migliaro, Fiorella, Sansone, Carlo
Lung ultrasound imaging is reaching growing interest from the scientific community. On one side, thanks to its harmlessness and high descriptive power, this kind of diagnostic imaging has been largely adopted in sensitive applications, like the diagn
Externí odkaz:
http://arxiv.org/abs/2011.00337
PRNU-based image processing is a key asset in digital multimedia forensics. It allows for reliable device identification and effective detection and localization of image forgeries, in very general conditions. However, performance impairs significant
Externí odkaz:
http://arxiv.org/abs/2001.06440
Due to limited computational and memory resources, current deep learning models accept only rather small images in input, calling for preliminary image resizing. This is not a problem for high-level vision problems, where discriminative features are
Externí odkaz:
http://arxiv.org/abs/1909.06751
Deep neural networks provide unprecedented performance in all image classification problems, taking advantage of huge amounts of data available for training. Recent studies, however, have shown their vulnerability to adversarial attacks, spawning an
Externí odkaz:
http://arxiv.org/abs/1902.07776
In the last few years, generative adversarial networks (GAN) have shown tremendous potential for a number of applications in computer vision and related fields. With the current pace of progress, it is a sure bet they will soon be able to generate hi
Externí odkaz:
http://arxiv.org/abs/1812.11842
With the ubiquitous diffusion of social networks, images are becoming a dominant and powerful communication channel. Not surprisingly, they are also increasingly subject to manipulations aimed at distorting information and spreading fake news. In rec
Externí odkaz:
http://arxiv.org/abs/1808.08426