Deep Generative Models

Deep Generative Models

Deep Generative Models created by 'mi03niza (Kromminga, Lukas) (Kromminga, Lukas)' on uploading a picture

Our expertise in Deep Generative Models is reflected by and related to several lecture, projects, as well as experts.

Deep Generative Models explained

Generative Adversarial Networks (GANs) and similar methods (e.g. Variational Auto Encoders) have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical image denoising, reconstruction, segmentation, data simulation, detection or classification. Furthermore, their ability to synthesize images at unprecedented levels of realism also gives hope that the chronic scarcity of labeled data in the medical field can be resolved with the help of these generative models.