Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/182488
Title: Unlearnable example with face images
Authors: Peng, Haohang
Keywords: Computer and Information Science
Issue Date: 2024
Publisher: Nanyang Technological University
Source: Peng, H. (2024). Unlearnable example with face images. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/182488
Abstract: This thesis focuses on the critical issue of image protection, with a particu- lar emphasis on safeguarding face images by introducing perturbations to these images. Deep learning models have demonstrated remarkable potential to drive significant advancements across various fields, including the generation of new images and the enhancement of object detection capabilities. However, alongside these advancements, there are inherent risks to personal privacy that cannot be overlooked. These risks arise through multiple avenues, especially in light of the rapid development of generative AI technologies such as stable diffusion, which empower individuals to create images using just a few reference pictures. To address this pressing problem, this research delves into the intricate rela- tionship between unlearnable examples (UEs) and deep learning models. We conduct a thorough analysis of how UEs can be effectively applied within the realm of generative AI. Furthermore, we extend our investigation to the use of UEs in object detection, aiming to ensure that models are unable to accurately detect or interpret these images, thereby enhancing privacy protection measures in the process.
URI: https://hdl.handle.net/10356/182488
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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