Deep learning plays a very important role in the research area in the field of Artificial
Intelligence (AI) and Machine Learning (ML) and many models have been developed based …

Generative adversarial networks are now a hot topic in the field of artificial intelligence.
GANs take their cue by including a generator and a discriminator learned using the …

In this paper we explore the synthesis of sound effects using conditional generative
adversarial networks (cGANs). We commissioned Foley artist Ulf Olausson to record a …

A comparatively novel advance field of deep learning is the Generative Adversarial Network
called GAN. These different types of networks if they start working in line with each other and …

Generative deep learning diffusion models have been attracting mainstream attention in the
field of 2D image generation. We propose a prototype which brings a diffusion network into …

We present an early prototype of a design system that uses Deep Learning methodology—
Conditional Variational Autoencoders (CVAE)—to arrive at custom design spaces that can …

Procedural content generation (PCG) can be applied to a wide variety of tasks in games,
from narratives, levels and sounds, to trees and weapons. A large amount of game content is …

Procedural content generation (PCG) can be applied to a wide variety of tasks in games,
from narratives, levels, and sounds to trees and weapons. A large amount of game content is …

Creating content for digital video game is an expensive segment of the development
process, and many techniques have been explored to automate it. Much of the generated …

Generative Adversarial Networks (GANs) have emerged as a significant player in generative
modeling by mapping lower-dimensional random noise to higher-dimensional spaces …