Abstract Generative Adversarial Networks (GANs) have been extremely successful in
various application domains such as computer vision, medicine, and natural language …

In the application of a bridge weigh-in-motion (WIM) system, the collected data may be
temporarily or permanently lost due to sensor failure or system transmission failure. The high …

Although deep learning-based models have achieved tremendous success in image-related
tasks, they are known to be vulnerable to adversarial examples---inputs with imperceptible …

The generative adversarial networks (GANs) have attracted substantial awareness as they
have the potential to generate the bulk of the unlabeled data. With the limited availability of …

Monitoring main entities in distributed systems is important for research, development, and
innovation activities involving those systems (offline analysis, simulated evaluation, etc.). In …

Pixel‐based generative image inpainting has been widely researched over recent years and
certain level of success via deep learning of feature representations and hallucinations of …

We propose a framework and impact of applying Machine Learning-based generated
imagery to augment data variations for firearm detection in cargo x-ray images. Deep …

Imperfections or defects inevitably occur in images due to inexperienced photographers,
inadequate methods of preservation, or even some deliberate hacking. Image restoration or …

Image inpainting is a promising but challenging approach that fills in huge free-form empty
areas in images. Most of the recent papers concentrate on splitting masked image into two …

Desde que aparecieron las redes GAN, se han realizado varias investigaciones sobre cómo
generar imágenes en diversos ámbitos, como la generación de imágenes, conversión de …