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Generative Adversarial Network for Nuclei Detection on Breast Cancer Histopathology Images
The semi-supervised GAN, or SGAN, model is an extension of the GAN architecture that involves the simultaneous training of a supervised discriminator, unsupervised discriminator, and a generator model. The result is both a supervised classification model that generalizes well to unseen examples and a generator model that outputs plausible examples of images from the domain. in this repository we tend to implement a simplified formation of that.
Image Processing Project on Exploring GANs. Here we have explored two different GANs - StackGAN for Text to Image Generation & SGAN for solving class imbalance