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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/dahsie/anomalie_detection
Ce projet est réalisé dans le cardre de mon projet académique de fin de cursus ingénieur informatique en data science. L'objectif est de réalisé la détection d'anomalie qui sont de types varié en utilisant les machine learning et le deep learning
anogan anomaly-detection autoencoder deep-learning ganomaly generative-adversarial-network isolation-forest local-factor-outlier neural-network one-class-svm python pytorch siamese-neural-network variational-autoencoder
Last synced: 15 Feb 2025
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
