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Skip to Search Results- 16Deep Learning
- 7Machine Learning
- 5Computer Vision
- 3Artificial Intelligence
- 3Remote Sensing
- 2Autoencoder
- 1Aghaei, Nikoo
- 1Bakhshinategh, Behdad
- 1Doosti Sanjani, Anahita
- 1Farruque, Nawshad
- 1Jahani Amiri, Ali
- 1Kapil, Rudraksh
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Spring 2022
Data augmentation is a strong tool for enhancing the performance of deep learning models using different techniques to increase both the quantity and diversity of training data. Cutout was previously proposed, in the context of image classification, as a simple regularization technique that...
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Advancing Forest Health Monitoring: Harnessing the Power of Deep Learning Computer Vision for Remote Sensing Applications
DownloadFall 2023
Forests provide immense economic, ecological, and societal values, making forest health monitoring (FHM) a crucial task for guiding conservation and management of these essential ecosystems. Drones have seen increased popularity in this domain due to their ability to collect high-resolution,...
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Spring 2021
The electrocardiogram is the standard tool for detecting cardiac abnormalities, such as atrial fibrillation, irregular complexes, and heart blocks. However, the interpretation of this data is an unsolved problem with discrepancies among panels of cardiologists and automated analysis requiring...
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Fall 2017
New machine learning methods and parallel computation opened the door to many applications in computer vision. While computer vision is progressing rapidly because of that, there are not as many and as successful real world applications in robotics. In this thesis, we investigate two possible...
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Design of a Course Recommender System as an Application of Collecting Graduating Attributes
DownloadFall 2016
In educational research, the term of Graduating Attributes has been used for the qualities, skills and understandings a university community agrees its students would develop. Having a description of Graduating Attributes is one of the ways through which universities can display the outcomes of...
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Image Registration with Homography: A Refresher with Differentiable Mutual Information, Ordinary Differential Equation and Complex Matrix Exponential
DownloadFall 2020
This work presents a novel method of tackling the task of image registration. Our algorithm uses a differentiable form of Mutual Information implemented via a neural network called MINE. An important property of neural networks is them being differentiable, which allows them to be used as a loss...
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Spring 2018
Semantic segmentation is about classifying every pixel in an image. In recent years, methods based on Fully Convolutional Networks (FCN) have dominated this field in terms of segmentation accuracy. We are interested in tackling the challenges that these methods are faced with. First, it is...
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Learning Deep Representations, Embeddings and Codes from the Pixel Level of Natural and Medical Images
DownloadFall 2013
Significant research has gone into engineering representations that can identify high-level semantic structure in images, such as objects, people, events and scenes. Recently there has been a shift towards learning representations of images either on top of dense features or directly from the...
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Spring 2023
The electrocardiogram (ECG) records the electrical activity of a patient’s heart movement. It is one of the standard routine healthcare tests as it is non-invasive and easy to apply. In this thesis, we analyze 2 million ECGs and over 260,000 patients’ health records from the Alberta Health...
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Spring 2023
Diffeomorphic image registration is important for medical imaging studies because of the properties like invertibility, smoothness of the transformation, and topology preservation/non-folding of the grid. Violation of these properties can lead to destruction of the neighbourhood and the...