This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
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Skip to Search Results- 1Ashfaque Mostafa, Tahjid
- 1Azari, Hossein
- 1Chen,Feng
- 1Faraji, Mehdi
- 1Firouzmanesh, Amirhossein
- 1Kamballur Kottayil, Navaneeth
- 3Machine Learning
- 2Deep Learning
- 2Image Processing
- 2Image Restoration
- 2InSAR Coherence Estimation
- 2Magnetic Resonance Imaging
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Fall 2014
Using motion capture data is an efficient way to generate and transmit 3D character animation. We explore the possibility of incorporating human perceptual factors in compression and synthesis of motion capture data in order to achieve a higher performance in different aspects including reducing...
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Fall 2024
Perceptual factors in vision can facilitate the development of more effective multimedia algorithms. In particular, the wide dynamic range of the human vision system is a motivation for developing image lighting enhancement algorithms. Image lighting enhancement can be achieved by capturing...
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Probabilistic Methods for Discrete Labeling Problems in Digital Image Processing and Analysis
DownloadFall 2012
Many problems in digital image processing and analysis can be interpreted as labeling problems, which aim to find the optimal mapping from a set of sites to a set of labels. A site represents a certain primitive, such as a pixel, while a label represents a certain quantity, such as disparity in...
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Fall 2022
The objective of signal decomposition is to extract and separate distinct signal components from a composite signal. Signal decomposition has been studied in many applications, such as image, video, audio, and speech signals. This thesis focuses on the category of signal decomposition on...
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Fall 2024
Distribution learning has long been a key area of research in computer vision. However, the potential of combining distribution learning with deep learning remains underexplored. To bridge this gap, this thesis discusses two proposed methods. The first, Differentiable Arithmetic Distribution...
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Scalable Solutions to Image Abnormality Detection and Restoration using Limited Contextual Information
DownloadFall 2020
Detecting and interpreting image abnormalities and restoring images are essential to many processing pipelines in diverse fields. Challenges involved include randomness and unstructured nature of image artefacts (from signal processing perspective) and performance constraints imposed by...
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Spring 2010
Skeletonization and segmentation are two important techniques for object representation and analysis. Skeletonization algorithm extracts the “centre-lines” of an object and uses them to efficiently represent the object. It has many applications in various areas, such as computer-aided design,...