In this article we explain what GauGANs are, and how their architecture and objective functions work. This is part of a series on Nvidia GauGANs.
From deepfakes and virtual celebrities to "fake news," we'll cover popular cases of media synthesis and the research publications detailing how it's done.
A dive into the challenges of data collection, and data labeling and the most efficient ways and tools to tackle them.
In this tutorial we'll train CycleGAN with Keras to generate images which age a subject's face, either forwards or backwards.
Deepfake technology is unlocking a new era of media production. As with all technologies, both positive and harmful use cases exist. As ethical technologists, we aspire to push the limits of what is possible, while minding the impact of the tools we create.
This article gives insights into the working mechanism of a Generative Adversarial Network and one of its popular variants, the Cycle Consistent Adversarial Network.
In this post, we’re going to be demonstrating how to to build a state of the art Bacterial Classification model on Gradient using the Fast.ai machine learning library.
In this post, we’ll build a machine learning pipeline to classify whether a patient has Pneumonia or not from chest x-ray images and then draw a heat-map on areas that the model used to make these decisions
Learn how to get access to models that have not yet been added to the Torchvision framework.
