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Skip to Search Results- 19Deep Learning
- 8Machine Learning
- 5Computer Vision
- 3Artificial Intelligence
- 3Remote Sensing
- 2Autoencoder
- 1Aghaei, Nikoo
- 1Atakishiyev, Shahin
- 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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Fall 2024
Autonomous driving, as a rapidly growing field, has received increasing attention from the general society and the automotive industry over the last two decades. However, road accidents involving autonomous vehicles have hindered societal acceptance and deployment of this technology on roads. As...
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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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Fall 2024
Procedural Content Generation via Machine Learning (PCGML) faces a significant hurdle that sets it apart from other ML problems, such as image or text generation, which is limited annotated data. For example, many existing methods for level generation via machine learning specifically require a...
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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...