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 …

Image restoration under adverse weather conditions has been of significant interest for
various computer vision applications. Recent successful methods rely on the current …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

This paper explores a better prediction target for BERT pre-training of vision transformers.
We observe that current prediction targets disagree with human perception judgment. This …

Brain tumor is one of the most dangerous cancers in people of all ages, and its grade
recognition is a challenging problem for radiologists in health monitoring and automated …

Recent successes in Generative Adversarial Networks (GAN) have affirmed the importance
of using more data in GAN training. Yet it is expensive to collect data in many domains such …

Although image inpainting, or the art of repairing the old and deteriorated images, has been
around for many years, it has recently gained even more popularity, because of the recent …

Image-to-image translation is considered a new frontier in the field of medical image
analysis, with numerous potential applications. However, a large portion of recent …

Recent advances in machine learning and prevalence of digital medical images have
opened up an opportunity to address the challenging brain tumor segmentation (BTS) task …