Conditional GAN (Generative Adversarial Network) with MNIST

Version 1.0.1 (939 KB) by 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
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Updated 12 Apr 2020

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[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 (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. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.1

Description updated

1.0.0