Conditional GAN (Generative Adversarial Network) with MNIST

Version 1.0.1 (939 ko) par Kenta
Hand-written digits were synthesized using a generative adversarial network called Conditional GAN. Conditional GANを用いて手書き数字を生成します
609 téléchargements
Mise à jour 12 avr. 2020

Afficher la licence

[English]
This example shows how to train a conditional generative adversarial network (CGAN) to generate digit images.This demo was created based on the Matlab official document entitled Train Conditional Generative Adversarial Network (CGAN)
https://jp.mathworks.com/help/deeplearning/ug/train-conditional-generative-adversarial-network.html
[Japanese]
このデモでは、Conditional GAN (Generative Adversarial Network)によって手書き数字を生成します。ラベル情報+画像にてネットワークを学習し、さらに画像を生成する際にもラベル情報を付加し、生成する画像のクラスを指定することができます。

Citation pour cette source

Kenta (2024). Conditional GAN (Generative Adversarial Network) with MNIST (https://www.mathworks.com/matlabcentral/fileexchange/74921-conditional-gan-generative-adversarial-network-with-mnist), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2020a
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Publié le Notes de version
1.0.1

Description updated

1.0.0