Generative models can synthesize photo-realistic images of a single object. For example, for
human faces, algorithms learn to model the local shape and shading of the face …

In recent years, the technological advances leading to the production of high-resolution
Synthetic Aperture Radar (SAR) images has enabled more and more effective target …

Despite success on a wide range of problems related to vision, generative adversarial
networks (GANs) often suffer from inferior performance due to unstable training, especially …

Identifying skin diseases, such as leprosy, Tinea Versicolor, and Vitiligo identification is one
of the challenging tasks. Therefore, skin disease identification success rate is comparatively …

Abstract Machine Learning (ML) is about computational methods that enable machines to
learn concepts from experiences. In handling a wide range of experiences ranging from data …

Remote sensing is the process of obtaining informative data about an object from afar. While
this applies to many different methods of data collection, as well as different domains to …

The Sinkhorn divergence, a smooth and symmetric normalization version of entropy-
regularized optimal transport (EOT) is a promising tool for Generative Adversarial Networks …