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Now showing items 11-18 of 18
An Ensemble Regression Approach For OCR Error Correction
(2017-04-11)
This thesis deals with the problem of error correction for Optical Character Recognation (OCR) generated text, or OCR-postprocessing: how to detect error words in a text generated from OCR process and to suggest the most ...
Analyzing Large Scale Wi-Fi Data Using Supervised and Unsupervised Learning Techniques
(2017-01-06)
With the increasing number of Wi-Fi enabled portable devices, and the ubiquitous Wi-Fi networks, analyzing multiple aspects of a population is becoming more insightful, inexpensive and non-intrusive. Network packets ...
A Machine Learning Approach to Forecasting Consumer Food Prices
(2017-08-24)
Building on the success of the Canada Food Price Report 2017 and its inclusion of a machine learning methodology, this research thesis posed and attempted to answer the following question, “What is the best way to predict ...
Modeling Activity Selection and Scheduling Behavior of Population Cohorts within an Activity-Based Travel Demand Model System
(2018-04-02)
Understanding the time-use activity patterns of population cohorts in the region will contribute greatly to modeling spatio-temporal urban transportation demand models. The research detailed in this dissertation focuses ...
Modelling Human Target Reaching using A novel predictive deep reinforcement learning technique
(2018-04-03)
It is hypothesized that the brain builds an internal representation of the world and its body. Moreover, it is well established that human decision making and instrumental control uses multiple systems, some which are ...
APPLICATION OF SUPPORT VECTOR MACHINES TO LONGITUDINAL FUNCTIONAL NEUROIMAGING DATA
(2016-12-15)
The principal objective of this thesis was to test a novel adaptation of the support vector machine (SVM), called a longitudinal support vector machine(LSVM), on longitudinal functional neuroimaging data. LSVM performance ...
Using Named Entities in Post-click News Recommendation
(2016-08-05)
With the growth of online news readers, many news websites use different signals to attract users' initial clicks. However, the problem of keeping users in the web site through post-click news recommendation is relatively ...
Using Machine Learning to Improve Motor Imagery Neurofeedback
(2015)
Machine Learning (ML) was employed to identify features in magnetoencephalography (MEG) recordings of 16 participants performing motor imagery (MI). ML was applied to data obtained using three methods: 1) two sources ...