Over the last few decades, rapid progress in AI, machine learning, and deep learning has
resulted in new techniques and various tools for manipulating multimedia. Though the …

Deep Learning (DL) has been effectively utilized in various complicated challenges in
healthcare, industry, and academia for various purposes, including thyroid diagnosis, lung …

Deep learning has been successfully applied to solve various complex problems ranging
from big data analytics to computer vision and human-level control. Deep learning advances …

The creation or manipulation of facial appearance through deep generative approaches,
known as DeepFake, have achieved significant progress and promoted a wide range of …

There are growing concerns about the potential for deepfake technology to spread
misinformation and distort memories, though many also highlight creative applications such …

Recent advancements in deep learning generative models have raised concerns as they
can create highly convincing counterfeit images and videos. This poses a threat to people's …

To properly contrast the Deepfake phenomenon the need to design new Deepfake detection
algorithms arises; the misuse of this formidable AI technology brings serious consequences …

Multimedia data manipulation and forgery has never been easier than today, thanks to the
power of Artificial Intelligence (AI). AI-generated fake content, commonly called Deepfakes …

In smart communities, social media allowed users easy access to multimedia content. With
recent advancements in computer vision and natural language processing, machine …

DeepFakes detection approaches have to be agnostic across generation type, quality, and
appearance to provide a generalizable DeepFakes detector. Limited generalizability will …