Browsing Graduate School - MU Theses and Dissertations (MU) by Thesis Advisor "Keller, James"
Now showing items 1-7 of 7
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Advances in automated surgery skills evaluation
(University of Missouri--Columbia, 2021)Training a surgeon to be skilled and competent to perform a given surgical procedure, is an important step in providing a high quality of care and reducing the risk of complications. Traditional surgical training is carried ... -
Advances in medical infrared thermography
(University of Missouri--Columbia, 2022)The association between illness and body temperature dates back to the beginnings of medicine. Over the last few years, infrared thermography has attracted increased attention in various medical applications due to ... -
Building environmentally-aware classifiers on streaming data
(University of Missouri--Columbia, 2022)The three biggest challenges currently faced in machine learning, in our estimation, are the staggering quantity of data we wish to analyze, the incredibly small proportion of these data that are labeled, and the apparent ... -
Data-driven methods for analyzing ballistocardiograms in longitudinal cardiovascular monitoring
(University of Missouri--Columbia, 2019)Cardiovascular disease (CVD) is the leading cause of death in the US; about 48% of American adults have one or more types of CVD. The importance of continuous monitoring of the older population, for early detection of ... -
Explainable pattern modelling and summarization in sensor equipped smart homes of elderly
(University of Missouri--Columbia, 2020)In the next several decades, the proportion of the elderly population is expected to increase significantly. This has led to various efforts to help live them independently for longer periods of time. Smart homes equipped ... -
Improved geo-referencing and prescreening for detection of buried explosive hazards in forward-looking infrared imagery
(University of Missouri--Columbia, 2014) -
Temporal decision making using unsupervised learning
(University of Missouri--Columbia, 2021)With the explosion of ubiquitous continuous sensing, on-line streaming clustering continues to attract attention. The requirements are that the streaming clustering algorithm recognize and adapt clusters as the data evolves, ...