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@@ -21,7 +21,7 @@ I decided to use a GAN (Generative Adverserial Network) model for this task.
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It consists of a generator to create images and a discriminator to determine whether the images are fake or not.
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And as the generator gets better and better at creating new images, the discriminator has more difficulty distinguishing them.
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I used this for reference, and adapted it to my own use case.
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It consists of a generator to create images and a discriminator to determine whether the images are fake or not.
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And as the generator gets better and better at creating new images, the discriminator has more difficulty distinguishing them.
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The images generated are CT scans of the lungs, either cancerous or non-cancerous.
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I used this for reference, and adapted it to my own use case.
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