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mhnazeri · Dec 21, 2023 · bb11016 · bb11016
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diff --git a/assets/img/publication_preview/musohu.gif b/assets/img/publication_preview/musohu.gif
diff --git a/assets/img/publication_preview/vertiwheelers-1400.webp b/assets/img/publication_preview/vertiwheelers-1400.webp
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diff --git a/assets/pdf/musohu.pdf b/assets/pdf/musohu.pdf
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-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.2">Jekyll</generator><link href="https://mhnazeri.github.io/feed.xml" rel="self" type="application/atom+xml" /><link href="https://mhnazeri.github.io/" rel="alternate" type="text/html" hreflang="en" /><updated>2023-12-21T02:53:55+00:00</updated><id>https://mhnazeri.github.io/feed.xml</id><title type="html">Mohammad</title><subtitle>Hello there, I&apos;m Mohammad. Welcome to my page!!!
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.2">Jekyll</generator><link href="https://mhnazeri.github.io/feed.xml" rel="self" type="application/atom+xml" /><link href="https://mhnazeri.github.io/" rel="alternate" type="text/html" hreflang="en" /><updated>2023-12-21T02:56:33+00:00</updated><id>https://mhnazeri.github.io/feed.xml</id><title type="html">Mohammad</title><subtitle>Hello there, I&apos;m Mohammad. Welcome to my page!!!
 </subtitle><entry><title type="html">SharinGAN</title><link href="https://mhnazeri.github.io/blog/2020/sharinGAN/" rel="alternate" type="text/html" title="SharinGAN" /><published>2020-07-29T21:16:41+00:00</published><updated>2020-07-29T21:16:41+00:00</updated><id>https://mhnazeri.github.io/blog/2020/sharinGAN</id><content type="html" xml:base="https://mhnazeri.github.io/blog/2020/sharinGAN/"><![CDATA[<p>Generative models especially with the emerge of <a href="https://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf">Generative Adversarial Networks (GANs)</a> have become the spotlight of Deep Learning in recent years. They have <a href="https://github.com/nashory/gans-awesome-applications">many applications in the wild</a> and sometimes they are just for <a href="https://theaisummer.com/deepfakes/">fun</a>.
 One fun application that I really liked, was the use of GAN to generate <a href="https://www.youtube.com/watch?v=8fnynVsR53k">fake Sharingans</a> (to read more about what Sharingan is please read <a href="https://naruto.fandom.com/wiki/Sharingan">this article</a>). Inspired by that video and PyTorch’s <a href="https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html">DCGAN tutorial</a>, in this post I’m going to show you how to generate sharingans step by step. You can download the PyTorch source code from <a href="https://github.com/mhnazeri/sharingan">here</a>. I highly recommend downloading the full source code because here I only explain important steps in writing a DL model, things such as config files are not discussed here. To read more about project configuration see my <a href="https://mhnazeri.github.io/blog/2020/parameter_management/">Hyper-parameter Management</a> article.</p>