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Generative Adversarial Network
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
- GitHub: https://github.com/topics/generative-adversarial-network
- Wikipedia: https://en.wikipedia.org/wiki/Generative_adversarial_network
- Released: June 10, 2014
- Related Topics: deep-learning, neural-network,
- Aliases: gan, generative-adversarial-networks,
- Last updated: 2025-02-13 00:12:09 UTC
- JSON Representation
https://github.com/marekpokropinski/pastagan
Style transfer convolutional neural network trained on FFHQ dataset and pasta images.
deep-learning generative-adversarial-network neural-network
Last synced: 24 Dec 2024
https://github.com/imvision12/dcgan-tensorflow
A Tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
dcgan gan generative-adversarial-network image image-generation tensorflow
Last synced: 14 Jan 2025
https://github.com/adeelh/gan-image-inpainting
Image Inpainting using a GAN (class project for Intelligent Visual Computing, Spring 2019)
cifar10 deep-learning gan generative-adversarial-network inpainting machine-learning
Last synced: 30 Jan 2025
