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Auxiliary Classifier – Generative Adversarial Networks in Keras

GPGPU Graphics Keras Machine Learning PhD Python

An experiment in augmenting a GAN architecture to use class-labels to guide image synthesis. The generator network takes as input a vector of 1 x 10 random values to use a seed for image synthesis, and a 1 x 10 one-hot vector for the class-label representing the desired digit.

In the above image the generated digits are made by giving the same 1 x 10 random vector for each image, with the y-axis varying the class-label, and the x-axis sweeping the value of one (common to all rows) randomly chosen column in the random vector between [0,1).

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