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Skip to Search Results- 144Machine Learning
- 19Artificial Intelligence
- 17Reinforcement Learning
- 15Deep Learning
- 10Computer Vision
- 10Natural Language Processing
- 2Wen, Junfeng
- 1Aghaei, Nikoo
- 1Al Dallal, Ahmed
- 1Al-Masri, Mohammad
- 1Alam Anik, Md Tanvir
- 1Alateeq, Majed Mohammad
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Spring 2024
As cancer is the leading global cause of death, an ongoing challenge is predicting an individual's cancer progression accurately, to facilitate personalized treatment planning. Individuals diagnosed with cancer may succumb to the illness or face cancer recurrence post-treatment. The first part of...
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Fall 2016
Current medical imaging professional training uses an apprenticeship model with students following an established doctor and viewing their cases, in what is called a practicum. This posses an issue as students are limited to the cases available during their practicum. To resolve this automated...
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Fall 2017
Network connectivity is an indispensable component of any computer related activities. Any computer-like machine is connected to some kind of a network, which is further connected to another computer network. Technological advances allow users to connect any devices and use multiple applications....
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Spring 2022
Numerical simulation and hybrid simulation are extensively used in earthquake engineering to evaluate the seismic response of structures under seismic loading. Despite the advances in computing power and the development of efficient integration algorithms in the past, numerical simulation...
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Deep Learning-based Forecasting and Energy Management Algorithms for Smart Grid Applications
DownloadFall 2023
With the increasing global problems concerning energy security and climate change, new challenges in social progress and human survival have come to the fore. Requiring no fuel, and being renewable and non-polluting, renewable energy (RE) resources, typically from photovoltaic and wind sources,...
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Fall 2011
The imbalanced learning problem occurs in a large number of economic and health domains of great importance; consequently, it has drawn a significant amount of interest from academia, industry, and government funding agencies. Several researchers have used stratification to alleviate this...
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Development of AI-based ergonomics risk assessment tools for harmonization of industrial work systems
DownloadFall 2023
Manufacturing industry workers face significant ergonomic risks due to poorly designed work systems. Consequently, it is crucial to periodically assess work systems to identify areas for improvement. However, the assessment process is often disregarded due to the absence of userfriendly...
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Fall 2012
Functional Magnetic Resonance Imaging (fMRI) measures the dynamic activity of each voxel of a brain. This dissertation addresses the challenge of learning a diagnostic classifier that uses a subject’s fMRI data to distinguish subjects with neuropsychiatric disorders from healthy controls. fMRI...
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Fall 2023
The problem of missing data is omnipresent in a wide range of real-world datasets. When learning and predicting on this data with neural networks, the typical strategy is to fill-in or complete these missing values in the dataset, called impute-then-regress. Much less common is to attempt to...
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Spring 2019
In this thesis we introduce a new loss for regression, the Histogram Loss. There is some evidence that, in the problem of sequential decision making, estimating the full distribution of return offers a considerable gain in performance, even though only the mean of that distribution is used in...