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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
- 13Deep learning
- 2Music information retrieval
- 1 Image denoising
- 13D Semantic Segmentation
- 1Artificial intelligence
- 1Cellulose-nanocrystal
- 1Burlet, Gregory D.
- 1He, Rui
- 1Hosseinzadeh Heydarabad,Sepideh
- 1Jiang, Honglin
- 1Karami, Mahdi
- 1Kushol, Rafsanjany
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A Comprehensive Study of Conditional Generative Adversarial Networks for Noise Reduction in Optical Coherence Tomography
DownloadFall 2024
Optical coherence tomography (OCT) has been widely adopted as an imaging modality for various clinical applications, such as breast cancer screening, retinal imaging, and vascular assessment, due to its non-invasive nature. However, OCT is affected by coherent speckle noise, which impairs OCT...
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A Framework for Synthesis of Musical Training Examples for Polyphonic Instrument Recognition
DownloadFall 2018
Music information retrieval (MIR), an interdisciplinary field involving the classifying or detection of structure in music, is essential for processing, indexing, querying and making recommendations from the vast amount of musical data available on the web and in audio library collections. Deep...
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Advances in Probabilistic Generative Models: Normalizing Flows, Multi-View Learning, and Linear Dynamical Systems
DownloadFall 2020
This thesis considers some aspects of generative models including my contributions in deep probabilistic generative architectures and linear dynamical systems. First, some advances in deep probabilistic generative models are contributed. Flow-based generative modelling is an emerging and highly...
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Fall 2024
Hip displacement is a prevalent disorder in children with cerebral palsy, defined as the lateral displacement of the femur head from under the acetabulum, and leads to severe pain and difficulties in daily activities. As a result, hip surveillance programs have been developed to monitor and...
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Deep Learning-Based Multi-Class Semantic Segmentation and Natural Language Scene Description of Multilane Rural Highways Using LiDAR Data
DownloadFall 2024
The increasing adoption of light detection and ranging (LiDAR) technology offers a promising avenue for automating the identification of road features. However, due to the complexity and density of the point cloud, most research focuses on extracting single or binary road elements from the LiDAR...
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Development of deep learning-based methods for rotating machinery fault diagnosis under varying speed conditions
DownloadSpring 2023
Rotating machines are widely used in industrial applications, such as driving motors in elevators and gearboxes in wind turbines. Machines in these applications often operate under varying speed conditions due to variable operation demand, ever-changing environment conditions and so on. As time...
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Fall 2024
Deep learning (DL) has become a leading subset of machine learning (ML) and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards multi-center neuroimaging studies to...
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Fall 2019
Emergent communication is a framework for machine language acquisition that has recently been utilized to train deep neural networks to develop shared languages from scratch and use these languages to communicate and cooperate. Previous work on emergent communication has utilized gradient-based...
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Fall 2015
Music transcription is the process of extracting the pitch and timing of notes that occur in an audio recording and writing the results as a music score, commonly referred to as sheet music. Manually transcribing audio recordings is a difficult and time-consuming process, even for experienced...
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Nanocrystal-based optical diffusers for white LED lighting: inverse design achieved by machine learning technologies
DownloadSpring 2023
Illumination receives a great deal of attention as white lighting-emitting diodes (WLEDs) become energy-efficient light sources in households and commercial buildings, on streets and highways, and at stadiums and construction sites. In general, lenses and mirrors are used to control the spatial...