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Exploring Photo Privacy Protection On Smartphones, David Darling
Exploring Photo Privacy Protection On Smartphones, David Darling
Computer Science and Computer Engineering Undergraduate Honors Theses
The proliferation of modern smartphone camera use in the past decade has resulted in unprecedented numbers of personal photos being taken and stored on popular devices. However, it has also caused privacy concerns. These photos sometimes contain potentially harmful information if they were to be leaked such as the personally identifiable information found on ID cards or in legal documents. With current security measures on iOS and Android phones, it is possible for 3rd party apps downloaded from official app stores or other locations to access the photo libraries on these devices without user knowledge or consent. Additionally, the prevalence …
Comparison Of Google Image Search And Resnet Image Classification Using Image Similarity Metrics, David Smith
Comparison Of Google Image Search And Resnet Image Classification Using Image Similarity Metrics, David Smith
Computer Science and Computer Engineering Undergraduate Honors Theses
In this paper, we compare the results of ResNet image classification with the results of Google Image search. We created a collection of 1,000 images by performing ten Google Image searches with a variety of search terms. We classified each of these images using ResNet and inspected the results. The ResNet classifier predicted the category that matched the search term of the image 77.5% of the time. In our best case, with the search term “forklift”, the classifier categorized 92 of the 100 images as forklifts. In the worst case, for the category “hammer”, the classifier matched the search term …
Training Machine Learning Agents In A 3d Game Engine, Diego Calderon
Training Machine Learning Agents In A 3d Game Engine, Diego Calderon
Computer Science and Computer Engineering Undergraduate Honors Theses
Artificial intelligence (AI) and video games benefit from each other. Games provide a challenging domain for testing learning algorithms, and AI provides a framework to designing and implementing intelligent behavior, which reinforces meaningful play. Medium and small studios, and independent game developers, have limited resources to design, implement, and maintain agents with reactive behavior. In this research, we trained agents using machine learning (ML), aiming to find an alternative to expensive traditional algorithms for intelligent behavior used in video games. We use Unity as a game engine to implement the environments and TensorFlow for the neural network training.
The 3d Abstract Tile Assembly Model Is Intrinsically Universal, Aaron Koch, Daniel Hader, Matthew J. Patitz
The 3d Abstract Tile Assembly Model Is Intrinsically Universal, Aaron Koch, Daniel Hader, Matthew J. Patitz
Computer Science and Computer Engineering Undergraduate Honors Theses
In this paper, we prove that the three-dimensional abstract Tile Assembly Model (3DaTAM) is intrinsically universal. This means that there is a universal tile set in the 3DaTAM which can be used to simulate any 3DaTAM system. This result adds to a body of work on the intrinsic universality of models of self-assembly, and is specifically motivated by a result in FOCS 2016 showing that any intrinsically universal tile set for the 2DaTAM requires nondeterminism (i.e. undirectedness) even when simulating directed systems. To prove our result we have not only designed, but also fully implemented what we believe to be …