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Graduate Defense: Hailee Kiesecker

March 10 @ 10:00 am - 11:00 am MST

Thesis Defense

Thesis Information

Title: Exploring the Capability of a Self-Supervised Conditional Image Generator for Image-To-Image Translation Without Labeled Data: A Case Study in Mobile User Interface Design

Program: Master of Science in Computer Science

Advisor: Dr. Tim Andersen, Computer Science

Committee Members: Dr. Edoardo Serra, Computer Science; and Dr. Casey Kennington, Computer Science


This research investigates the effectiveness of a conditional image generator trained on a restricted number of unlabeled images for image-to-image translation in computer vision. While previous research has focused on using labeled data for image labeling in conditional image generation, this study proposes an original framework that utilizes self-supervised classification on generated images. The proposed approach, which combines Conditional GAN and Semantic Clustering, showed promising results. However, this study has several limitations, including a limited dataset and the need for significant computational power to generate a single UI design. Further research is needed to optimize the performance of the proposed approach for real-world applications.