Search
Skip to Search Results- 76Machine learning
- 13Image processing
- 5Artificial intelligence
- 4Directionality
- 4Reinforcement learning
- 3Computer vision
- 2White, Martha
- 1Afaghi, Mohammad
- 1Ajallooeian, Mohammad Mahdi
- 1Alexandra Marie Claire Beatty
- 1Alinezhad, Haniyeh Seyed
- 1Allen, Felicity R
-
The challenge of applying machine learning techniques to diagnose schizophrenia using multi-site fMRI data
DownloadSpring 2017
One of the main challenges for the use of machine learning techniques in neuroimaging data is the small n, large p problem. Datasets usually contain only a few hundreds of instances (n), each of which is described using hundreds of thousands of features (p). In this dissertation, we explore the...
-
Fall 2012
In a partial-monitoring game a player has to make decisions in a sequential manner. In each round, the player suffers some loss that depends on his decision and an outcome chosen by an opponent, after which he receives "some" information about the outcome. The goal of the player is to keep the...
-
Spring 2018
Decision-making problems with two agents can be modeled as two player games, and a Nash equilibrium is the basic solution concept describing good play in adversarial games. Computing this equilibrium solution for imperfect information games, where players have private, hidden information, is...
-
Fall 2016
This thesis focuses on the experimental and theoretical study of various rare-earth transition-metal germanides that contain three or four components. Ternary and quaternary germanides were synthesized through various methods, including direct reaction of the elements, arc-melting, and flux...
-
Fall 2021
Pressure swing adsorption (PSA) processes are an industrially mature low energy consumption pathway for gas separations. Due to their performance being linked to the separation media, they provide an additional degree of freedom for process design. They are difficult to accurately model due to...
-
Fall 2023
The recognition performance of Optical Character Recognition (OCR) models can be sub-optimal when document images suffer from various degradations. Supervised learning-based methods for image enhancement can generate high-quality enhanced images. However, these methods require the availability of...
-
Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Diagnose ADHD and Autism
DownloadFall 2014
A clinical tool that can diagnose psychiatric illness using functional or structural magnetic resonance (MR) brain images would greatly assist physicians. Here, we propose a learning algorithm that uses the histogram of oriented gradients (HOG) features of MR brain images, as well as personal...
-
Using Machine Learning to Identify Common Engagement-Related Behaviours Demonstrated by Older Adults with Dementia While Playing Mobile Games
DownloadFall 2022
Background: Dementia causes impairment of a person’s memory, cognitive abilities, and behaviour, making it difficult for a person to complete daily tasks. Dementia affects the behavioural, psychological, and social dimensions of older adults living with the disease. Older adults living with...
-
Fall 2023
Oftentimes, machine learning applications using neural networks involve solving discrete optimization problems, such as in pruning, parameter-isolation-based continual learning and training of binary networks. Still, these discrete problems are combinatorial in nature and are also not amenable to...
-
Spring 2024
Wildfires occurring in proximity to urban areas pose a potential risk to the safety and wellbeing of the population, while also carrying the potential for substantial economic damage through the destruction of infrastructure and private property. Canada, given its unique geographical and climatic...