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Skip to Search Results- 49Deep Learning
- 21Machine Learning
- 9Computer Vision
- 8Artificial Intelligence
- 3Convolutional Neural Network
- 3Image Classification
- 2Shahpouri, Saeid
- 1Aghaei, Nikoo
- 1Akbari, Mojtaba
- 1Alla, Hemanth Reddy
- 1Amini, Iman
- 1Atakishiyev, Shahin
- 47Graduate and Postdoctoral Studies (GPS), Faculty of
- 47Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 1Concordia University of Edmonton
- 1Concordia University of Edmonton/Master of Science in Information Technology Project Reports (Concordia University of Edmonton)
- 1Mechanical Engineering, Department of
- 1Mechanical Engineering, Department of/Journal Articles (Mechanical Engineering)
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Fall 2024
Deep learning-based segmentation plays a crucial role in computer and robot vision. Traditional approaches have predominantly relied on RGB (i.e., color) imagery, given its widespread availability and usage. However, the innate issues with color imagery, such as cluttered backgrounds and poor...
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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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Fall 2019
Search query understanding is a trending topic in the field of Information Retrieval (IR). The goal is to learn higher-level representations for the intents or concepts behind a search query and utilize these representations to further enhance down-stream services like content recommendation....
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Fall 2019
Object detection is an image processing technology to detection different classes of objects using computer vision, i.e. putting bounding boxes over objects from a camera video feed. A landmark detection method was the Viola-Jones Algorithm introduced in 2001. The object classifier in this...
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Fall 2024
Operated under changing wind speed and harsh environment conditions, the rotating parts in wind turbine gearboxes, such as gears and bearings, will deteriorate and become faulty over time. By conducting real-time and accurate fault detection and diagnosis before significant failures occur, we can...
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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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Spring 2019
While deep learning has proven to be a powerful new tool for modeling and predicting a wide variety of complex phenomena, those models remain incomprehensible black boxes. This is a critical impediment to the widespread deployment of deep learning technology, as decades of research have found...
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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...