0000000000095759
AUTHOR
Bjørn-inge Støtvig Thoresen
NeuralHash for Privacy Preserving Image Analysis
This thesis aims to investigate how Apple's NeuralHash algorithm can be used in the context of facial recognition to improve privacy in facial recognition systems. Existing facial recognition solutions rely on having facial images available to match identities, however, this can impair the privacy of individuals, as the images can contain sensitive information that the individuals do not want to share. In this thesis, the NeuralHash algorithm is used to hash facial images of subjects in the ColorFERET Dataset, and the NeuralHashes are compared to attempt to identify the same subjects and different subjects. The NeuralHash algorithm's ability to hide information is also investigated, in addi…
Generating Levels and Playing Super Mario Bros. with Deep Reinforcement Learning Using various techniques for level generation and Deep Q-Networks for playing
Master's thesis in Information- and communication technology (IKT590) This thesis aims to explore the behavior of two competing reinforcement learning agents in Super Mario Bros. In video games, PCG can be used to assist human game designers by generating a particular aspect of the game. A human game designer can use generated game content as inspiration to build further upon, which saves time and resources. Much research has been conducted on AI in video games, including AI for playing Super Mario Bros. Additionally, there exists a research field focused on PCG for video games, which includes generation of Super Mario Bros. levels. In this thesis, the two fields of research are combined to…