Generative deep learning algorithms have progressed to a point where it is difficult to tell the
difference between what is real and what is fake. In 2018, it was discovered how easy it is to …

Seeing is not believing anymore. Different techniques have brought to our fingertips the
ability to modify an image. As the difficulty of using such techniques decreases, lowering the …

The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …

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 …

Techniques for creating and manipulating multimedia information have progressed to the
point where they can now ensure a high degree of realism. DeepFake is a generative deep …

Learning to reject is a special kind of self-awareness (the ability to know what you do not
know), which is an essential factor for humans to become smarter. Although machine …

Creating deepfakes has rapidly become easier and more accessible due to advancements
in hardware and computing. The harmful nature of deepfakes urges immediate action to …

Remarkable advances have been made in deep learning, leading to the emergence of
highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models …

With the development of computer vision and deep learning technologies, rapidly expanding
approaches have been introduced that allow anyone to create videos and pictures that are …

This study conducts research on deepfakes technology evolution and trends based on a
bibliometric analysis of the articles published on this topic along with six research questions …