Description

 To introduce students to Generative Adversarial Networks (GANs) and their applications in various domains.  To provide students with an understanding of the theoretical foundations, architectural complexities, and practical implementations of GANs.  To explore the diverse applications of GANs in image synthesis, style transfer, data augmentation, and beyond.

Program

Artificial Intelligence 132 CRs

Objectives

• This course introduces students to the fascinating world of GANs, which consist of two neural networks—generative and discriminative—competing in a game. From understanding loss functions to architectural intricacies, students will explore applications in image synthesis, style transfer, and data augmentation. Labs and workshops will enhance understanding by allowing students to build and refine their models.