Abstract Generative Adversarial Networks (GAN) have led to the generation of very realistic
face images, which have been used in fake social media accounts and other disinformation …

In the last few years, there has been a growing expectation created about the analysis of
large amounts of data often available in organizations, which has been both scrutinized by …

Deepfake refers to realistic, but fake images, sounds, and videos generated by articial
intelligence methods. Recent advances in deepfake generation make deepfake more …

Generative adversarial networks (GANs) can be used to generate a photo-realistic image
from a low-dimension random noise. Such a synthesized (fake) image with inappropriate …

With the powerful deep network architectures, such as generative adversarial networks, one
can easily generate photorealistic images. Although the generated images are not …

Deepfake network is a prominent topic of research as an application to various systems
about security measures. Although there have been many recent advancements in facial …

With the proliferation of face image manipulation (FIM) techniques such as Face2Face and
Deepfake, more fake face images are spreading over the internet, which brings serious …

Full face synthesis and partial face manipulation by virtue of the generative adversarial
networks (GANs) and its variants have raised wide public concerns. In the multi-media …

The introduction of publicly available large-scale datasets and advances in generative
adversarial networks (GANs) have revolutionized the generation of hyper-realistic facial …

A novel analysis-prediction (ANP) approach for geometrically nonlinear problems of solid
mechanics is for the first time proposed in this paper. The key concept of this approach is:(1) …