AkulMehra
Hello world of Machine learning
Classifying Handwritten digits using image processing and machine learning
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Generative Adversarial Networks (GAN's) are a class of neural networks which allow a network to generate data with the same internal structure as other data.
A GAN has two parts in it:
The generator that generates images and the discriminator that classifies real and fake images.
Convolutional Neural Network(CNN)
Convolutional Neural Networks are made up of neurons that have learnable weights and biases. Each neuron receives some inputs, performs a dot product and optionally follows it with a non-linearity.
How we goanna use CNN in GAN's?
Generator :- It uses De-CNN
Discriminator:- It uses CNN
Highest probability is the selected value.
And why they rock !!
DiscoGAN stands for
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks (Link)
(a) Translation of gender in Facescrub dataset and CelebA dataset
(b) Blond to black and black to blond hair color conversion in CelebA dataset.
(c) Wearing eyeglasses conversion in CelebA dataset
DiscoGAN
After iteration: 11,000
Handbags -> Shoes -> Handbags
After iteration: 22000
Image -> Segmentation -> Image
AkulMehra
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