With the latest advances in deep learning-based generative models, it has not taken long to
take advantage of their remarkable performance in the area of time series. Deep neural …

The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …

With the massive proliferation of data-driven algorithms, such as deep learning-based
approaches, the availability of high-quality data is of great interest. Volumetric data is very …

Generative Adversarial Networks (GANs) are a remarkable creation with regard to deep
generative models. Thanks to their ability to learn from complex data distributions, GANs …

Abstract Single Image Super Resolution (SISR) is a process to obtain a high pixel density
and refined details from a low resolution (LR) image to get upscaled and sharper high …

Abstract Advances in Deep Learning (DL), Big Data and image processing have facilitated
online disinformation spreading through Deepfakes. This entails severe threats including …

As we transition from the 5G epoch, a new horizon beckons with the advent of 6G, seeking a
profound fusion with novel communication paradigms and emerging technological trends …

Along with the high demand for network connectivity from both end-users and service
providers, networks have become highly complex; and so has become their lifecycle …

Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …

Traditional data-driven intelligent fault diagnosis methods for rotating component commonly
assume that sufficient labeled data is available. However, the rotary machine works in a …