Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

Single image super-resolution (SISR) has played an important role in the field of image
processing. Recent generative adversarial networks (GANs) can achieve excellent results …

GAN's are playing an important role in creating and generating a new set of data from the
previously available content. GAN models are impressive in the results for image and video …

This paper offers an insightful examination of how currently top-trending AI technologies, ie,
generative artificial intelligence (Generative AI) and large language models (LLMs), are …

Quantum mechanics studies nature and its behavior at the scale of atoms and subatomic
particles. By applying quantum mechanics, a lot of problems can be solved in a more …

The existence of specular highlights hinders high-level computer algorithms. In this paper,
we propose a novel approach to remove specular highlights from a single grayscale image …

In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

This paper presents TrajGen, an approach to generate artificial datasets of mobility
trajectories based on an original trajectory dataset while retaining the utility of the original …

In this paper, we propose the quantum semi-supervised generative adversarial network
(qSGAN). The system is composed of a quantum generator and a classical …