Birkbeck Knowledge Lab Seminar: Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification
When:
—
Venue:
Online
We present an algorithm for one-class classification based on binary classification of the target class against synthetic samples. We use a process inspired by Generative Adversarial Networks (GANs) in order to both acquire synthetic samples and to build the one-class classifier. The first objective is achieved by leading the generator’s output into close vicinities of the target class region. For the second objective, we obtain a one-class classifier by generating an ensemble of discriminators obtained from the GAN’s training process. Our approach is tested on public domain datasets producing promising results when compared to other state-of-the-art methods.
Contact name:
George Magoulas