The breakthrough brought by generative adversarial networks (GANs) in computer vision
(CV) applications has gained a lot of attention in different fields due to their ability to capture …

Abstract Generative Adversarial Networks (GANs) produce impressive results on
unconditional image generation when powered with large-scale image datasets. Yet …

Background and objectives: Visual analysis of cell morphology has an important role in the
diagnosis of hematological diseases. Morphological cell recognition is a challenge that …

Recent advances in the industrial inspection of textured surfaces—in the form of visual
inspection—have made such inspections possible for efficient, flexible manufacturing …

Texture recognition is a challenging visual task since its multiple primitives or attributes can
be perceived from the texture image under different spatial contexts. Existing approaches …

A major difficulty in integrating large scale wind power generation in an electrical power
system is that wind generated power appears to be erratic, intermittent, and volatile. In this …

Synthesizing larger texture images from a smaller exemplar is an important task in graphics
and vision. The conventional CNNs, recently adopted for synthesis, require to train and test …

Real-time graphics applications require high-quality textured materials to convey realism in
virtual environments. Generating these textures is challenging as they need to be visually …

Existing texture synthesis methods focus on generating large texture images given a small
texture sample. But such samples are typically assumed to be highly curated: rectangular …

We propose Neural Brushstroke Engine, the first method to apply deep generative models to
learn a distribution of interactive drawing tools. Our conditional GAN model learns the latent …