There are 2 repositories under dcgan-keras topic.
Conditional face generation experiments using GAN models on CelebA dataset.
Generation Of Synthetic Images From Fashion MNIST Dataset With DCGANs In Keras.
DCGAN Projects Repository implemented using Keras. (Includes pre-trained model)
In this script, we use Deep Convolutional Generative Adversarial Networks (DCGANs) to generate new images that resemble CIFAR10 dataset images.
DCGAN to generate Anime Character's Faces
Coursera hand held project to understand the deepfakes using keras (DCGAN)
Create images of Pokemon using a Deep Convolutional Generative Adversarial Network.
Using DCGAN to generate abstract art
This 'Generative Adversarial Network' project was implemented in grad course CSE-676 : Deep Learning [Fall 2019 @UB_SUNY] Course Instructor : Sargur N. Srihari(https://cedar.buffalo.edu/~srihari/)
DCGAN to generate Anime Character's Faces
deep convolutional generative adversarial network for FashionMNIST dataset with Keras and keras-adversarial
Implementation of DCGAN model to train a neural network on mnist dataset and generate fake handwritten digits close enough to the real images from the dataset.
Generate Anime Style Face Using DCGAN and Explore Its Latent Feature Representation
Training a DCGAN to generate new images of faces that look realistic as possible.
The combined method between applying the CNNs to GANs models is called Deep Convolutional Generative Adversarial Networks (DCGANs).
Keras implementation of dcgan, wgan and wgan-gp with digit-MNIST dataset for tutorials.