Adidas Hackathon Amsterdam 2018: Customize products with unique style transfer

Create new and unseen Anime faces using Generative Adversarial Networks (Gans) Model implemented using Tensorlow and Python

A PhotoReaslistic AI GAN model to generate photorealistic faces on a large scale

This model is basically used for deep learning.In this models i have used DCGANs and it are more powerful then ordinary GANs. Output image are saved at every 100 epochs which are stored in gan_images folder. Well I had not uploaded every images in it.Images within 9000 epochs are included in it. It will take almost 1 or 2 days to learn or to tra…

TensorFlow implementation of DCGAN

Regret Minimization Approach to training "Deep Convolution Generative Adversial Network" on MNIST Dataset.

Experiment on making of icons with a GAN

This repository explains how to train DCGAN with own dataset based on

Using DCGAN and Ensemble Learning to classify the difference of the disease of different mangoes.

TF v2.3.0 DCGAN implementation trained on Anime face dataset.

Generating high-resolution adversarial images with GAN

The Lentach logo generator. #MachineLearningFun

The Generative Adversarial Networks with Python would serve as our primary reference throughout the project. The models would be trained on the MNIST dataset. The official TensorFlow framework and documentation will be used to implement the different architectures on Python. These papers would be used to implement various evaluation met

Fake face generation using DCGAN

Damaged image restauration using a GAN model with a U-Net with skip connection autoencoder as a generator

Create images of Pokemon using a Deep Convolutional Generative Adversarial Network.

GAN example