nn_gan.jpg
The image displays a flowchart diagram titled "Generative Adversarial Network" in large black sans-serif font at the top center against a white background. The diagram illustrates the process of training this type of machine learning model using arrows and labeled boxes.

On the far left side, there is a vertical stack of eight colored rectangular blocks enclosed by a bracket labeled "Latent Space". From top to bottom, the colors of these blocks are light blue, grey, green, yellow, magenta, grey, blue, and pink. An arrow points from this stack to the right, leading into a circle containing a plus sign symbol. Below this circle, an upward-pointing arrow is labeled "Noise", indicating that noise is added to the latent space input.

The output of this addition flows into a rounded rectangle in the middle-left area labeled with a large letter "G" and the word "Generator". An arrow exits the right side of this Generator box, labeled "Generated Fake Samples".

Above the Generator flow, there is another input source labeled "Real Samples". This consists of four overlapping squares stacked diagonally. The colors from back to front appear to be light blue, green, beige, and light blue.

The line representing the "Real Samples" and the line for "Generated Fake Samples" converge at a junction point marked by two black dots. Near this junction, there are small dashed arrows indicating interaction or comparison between these inputs before they proceed to the next stage.

Both streams enter a rounded rectangle on the right side labeled with a large letter "D" and the word "Discriminator".

An arrow points from the Discriminator to a diamond shape with a dashed outline containing the text "Is D Correct?".

From the bottom of this diamond, a dotted line loops back to the left. This path is labeled "Fine Tune Training". The line goes down and then turns left. One segment of this loop has an arrow pointing up into the bottom of the Discriminator box. The main path continues further left and has an arrow pointing up into the bottom of the Generator box, completing the feedback loop for training.
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