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Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 165Machine Learning
- 22Artificial Intelligence
- 21Reinforcement Learning
- 20Deep Learning
- 11Natural Language Processing
- 10Computer Vision
- 2Jacobsen, Andrew
- 2Wen, Junfeng
- 1Aghaei, Nikoo
- 1Al Dallal, Ahmed
- 1Al-Masri, Mohammad
- 1Alam Anik, Md Tanvir
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Automated Rod Length Measurements on Radiographs and Sonograms in Children with Early Onset Scoliosis
DownloadFall 2024
Early Onset Scoliosis (EOS) is a medical condition that is defined as a lateral curvature of the spine with vertebral rotation in children under age 10. Approximately 2-3% of children worldwide have scoliosis. Surgical intervention is the most effective management to treat these children who have...
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Fall 2012
Automated sports commentary is a form of automated narrative and human-computer interaction. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in progress. We introduce a system called the...
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Fall 2018
Videogames often use artificial intelligence to control characters in the game world. In doing so, videogames require one or more agents to navigate from their current location to some desired goal location without collisions. We explore improving algorithm performance in both single and...
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Automatic Detection of Underground Objects in Ground Penetrating Radar Images using Machine Learning
DownloadFall 2021
The population increase has stimulated the need for the creation and expansion of existing urban infrastructures such as sewer, water, power and telecommunication lines. In order to support this need, multiple efforts to find sustainable solutions that support the urbanization trend have been...
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Spring 2022
Nowadays, with the rapid development of science and technology, human healthcare has become a hot topic and attracts more and more attention. A lot of researchers work on different technologies to contribute to our healthcare no matter disease diagnosis and prognosis or disease treatment. In this...
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Spring 2022
Molecular self-assembly is the basis of structure in Nature. While of far less complexity than a natural system, the same physical rules apply to simple synthetic designed systems that spontaneously form self-assembled structures and patterns. The self-assembly of block copolymers (BCPs) is an...
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Spring 2024
As cancer is the leading global cause of death, an ongoing challenge is predicting an individual's cancer progression accurately, to facilitate personalized treatment planning. Individuals diagnosed with cancer may succumb to the illness or face cancer recurrence post-treatment. The first part of...
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Fall 2024
Reinforcement learning has been widely applied in different control tasks. However, its performance often faces the challenge of low sample efficiency. Introducing human prior knowledge is often seen as a possible solution, such as behaviour cloning, learning from advice, and inverse...
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Fall 2024
The success of deep learning is partly due to the sheer size of modern models. However, such large models strain the capabilities of mobile or resourceconstrained devices. Ergo, reducing the resource demands of AI models is essential before AI can be deployed on such devices. One promising...
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Fall 2024
This thesis presents a novel data-driven approach for identifying categoryselective regions in the human brain that are consistent across multiple participants. By leveraging a massive fMRI dataset and a multi-modal (language and image) neural network (CLIP), we trained a highly accurate...