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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
- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 83Machine Learning
- 76Reinforcement Learning
- 42Artificial Intelligence
- 37Machine learning
- 24Natural Language Processing
- 23reinforcement learning
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Fall 2022
Monte Carlo Tree Search (MCTS) is an extremely successful search-based frame- work for decision making. With an accurate simulator of the environment’s dynamics, it can achieve great performance in many games and non-games applications. However, without a perfect simulator, the performance...
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Spring 2023
The intent of this thesis is to develop a high-performance open-source system that plans with a learned model and to understand the algorithm through extensive analysis. We formulate the problem of maximizing accumulated rewards in Markov Decision Processes, and we frame playing games as such...
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Spring 2016
Morphologically complex languages such as Arabic pose several challenges in Natural Language Processing (NLP) due to their complexity and token sparsity. Most techniques approach the problem by transforming the words of the language from their sparse surface form representation to a less sparse...
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Spring 2019
Motion analysis is very important and it has extensive applications in surveillance, smart rooms, and so on. Different types of sensors can be used to capture the required information. One can use eye-gaze system to record eye motion or Kinect or Leap Motion sensors to record 3d keypoints. Even a...
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Spring 2018
High blood pressure (BP) is the leading cause of death and disability in the world, affecting nearly 1.5 billion adults. It leads to many complications, including stroke, heart failure, kidney disease, and coronary disease. In current clinical practice, BP is measured either invasively by an...
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Fall 2016
Salzvedel Furtado Junior, Antonio Carlos
Motion capture (MoCap) data has always been one of the most important components in the entertainment industry, being widely employed in animated movies and games. Given technological advancements in motion capture technologies, it has been successfully applied to other areas, such as surgical...
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Spring 2016
This thesis applies the Monte Carlo Random Walk method (MRW) to motion planning. We explore different global and local restart strategies to improve the performance. Several new algorithms based on the MRW approach, such as bidirectional Arvand and optimizing planner Arvand*, are introduced and...
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Spring 2014
Monte Carlo tree search (MCTS) combined with the upper confidence bounds applied to trees (UCT) algorithm has brought forth many advances in game related AI. This includes general game players and programs for specific games such as Amazons, Arimaa, and Go. However, there often is a need for...
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Moving Object Detection Using Unsupervised and Weakly Supervised Neural Networks in Videos with Illumination Changes and Dynamic Background
DownloadFall 2023
Background subtraction is a crucial task in computer vision applications, such as video surveillance, traffic monitoring, autonomous navigation, and human-computer interaction. This approach involves acquiring a background model to separate moving objects and the background from an input image....