Creating logo images using Generative Adversarial Networks (GANs). This project uses GANs models to produce new logo images. It works by trying to mimic real-world images collected …

Mar 3, 2020 · To put it bluntly, General Adversarial Networks (GANs) are hard. Once you have finished navigating the swamp of detailed Mathematics you then have to get over the cryptic …

Feb 6, 2024 · In this blog post, I will show you how to logo design using GANs, introduce you to Brandmark, a deep learning tool for logo design, discuss the future of logo design using GANs, …

Dec 12, 2017 · We propose the use of synthetic labels obtained through clustering to disentangle and stabilize GAN training. We are able to generate a high diversity of plausible logos and we …

In a GAN, two neural networks compete with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate …

Mar 10, 2025 · What is a Generative Adversarial Network(GAN)? A GAN consists of two neural networks: Generator: Creates new data samples. Discriminator: Evaluates whether the …

Training Generative Adversarial Networks (GANs) for logo synthesis on such multi-modal data is not straightforward and results in mode collapse for some state-of-the-art methods. We …

We propose LoGAN: an improved auxiliary classifier Wasserstein generative adversarial neural network (with gradient penalty) that is able to generate logos conditioned on twelve different …

Nov 5, 2018 · In this post I’ll discuss Generative Adversarial Networks (GANs). Like VAEs, GANs are made up of two models: a generator and a discriminator and can also be used to generate …

Feb 13, 2021 · For this project I utilised GAN technologies with the aim of creating/generating seemingly authentic business logos. This portfolio post spotlights a project which was …