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| author | Soumith Chintala <soumith@gmail.com> | 2015-11-16 19:11:29 +0300 |
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| committer | Soumith Chintala <soumith@gmail.com> | 2015-11-16 19:11:29 +0300 |
| commit | 08d9bc581b542c405d2c4caedf180e1a6dee3132 (patch) | |
| tree | 375e9e5d3ff1e417403ea8ee1bbb7b5444b69166 /blog | |
| parent | 613a1e0f42ad55d1180e6e6e59959af3e56d2885 (diff) | |
Update 2015-11-13-gan.md
Diffstat (limited to 'blog')
| -rw-r--r-- | blog/_posts/2015-11-13-gan.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/blog/_posts/2015-11-13-gan.md b/blog/_posts/2015-11-13-gan.md index aa64056..cc7221b 100644 --- a/blog/_posts/2015-11-13-gan.md +++ b/blog/_posts/2015-11-13-gan.md @@ -12,7 +12,7 @@ picture: https://raw.githubusercontent.com/torch/torch.github.io/master/blog/_po In this blog post we'll implement a generative image model that converts random noise into images of faces! [Code available on Github](https://github.com/skaae/torch-gan). -<p align='center'><img width="75%" src="https://raw.githubusercontent.com/torch/torch.github.io/master/blog/_posts/images/model.png"></p> +<p align='center'><img width="100%" src="https://raw.githubusercontent.com/torch/torch.github.io/master/blog/_posts/images/model.png"></p> For this task, we employ a [Generative Adversarial Network](http://arxiv.org/abs/1406.2661) (GAN) [1]. A GAN consists of two components; a *generator* which converts random noise into images and a *discriminator* which tries to distinguish between generated and real images. Here, 'real' means that the image came from our training set of images in contrast to the generated fakes. |