Conditional GAN (Generative Adversarial Network) with MNIST

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

You are now following this Submission

[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。

Cite As

Kenta (2026). Conditional GAN (Generative Adversarial Network) with MNIST (https://uk.mathworks.com/matlabcentral/fileexchange/74921-conditional-gan-generative-adversarial-network-with-mnist), MATLAB Central File Exchange. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0.1

Description updated

1.0.0