Browsing Theses (MU) by Thesis Advisor "Keller, James M."
Now showing items 1-20 of 22
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Automatic detection of explosive devices in infrared imagery using texture with adaptive background mixture models
(University of Missouri--Columbia, 2011)Infrared cameras can be used to image unpaved roads containing buried explosive hazards where detection relies upon differences between settled and disturbed soil in addition to thermal emissivity. Used is a variation of ... -
Automatic explosive hazard detection in FL-LWIR and FL-GPR data
(University of Missouri--Columbia, 2012)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Detection of land mines and other buried explosive hazards, has been, and continues to be, a serious issue for military and civilian organizations. A ... -
Detecting explosive hazards in 3D radar imaging through slice based feature extraction and sequential learning
(University of Missouri--Columbia, 2018)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This thesis provides the history and framework of detecting explosive hazards from three-dimensional radar by extracting features through a slice-based ... -
Estimation and tracking of elder activity levels for health event prediction
(University of Missouri--Columbia, 2009)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Significant declines in quality of life for elders in assisted living communities are typically triggered by health events. Given the necessary ... -
Estimation of dynamic detector confidence thresholds in SAS imagery using mixture models
(University of Missouri--Columbia, 2019)As machine learning has matured over the years, more and more safety critical tasks have been entrusted to computers. Automated target recognition (ATR), the problem of identifying explosive hazards on the sea?oor, is one ... -
An evolutionary framework for matching geospatial object configurations
(University of Missouri--Columbia, 2012)This thesis presents a framework for modeling and comparing the spatial configuration of sets containing two-dimensional geospatial objects. This situation can arise in the conflation of a hand or machine drafted map to a ... -
Experimental study of random projections below the JL limit
(University of Missouri--Columbia, 2015)Random projection is a method used to reduce dimensionality of desired objects with pair-wise distances preserved at a relatively high probability. The mathematical theory behind this is called the Johnson-Lindenstrauss ... -
The family of sequential possibilistic one-mean clustering algorithms
(University of Missouri--Columbia, 2018)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The possibilistic c-means (PCM) was developed as an extension of the fuzzy c-means (FCM) clustering algorithm by abandoning the membership sum-to-one ... -
Fractal Analysis of Seafloor Textures for Target Detection in Synthetic Aperture Sonar Imagery
(University of Missouri--Columbia, 2018)Fractal analysis of an image is a mathematical approach to generate surface related features from an image or image tile that can be applied to image segmentation and to object recognition. In undersea target countermeasures, ... -
The histogram of partitioned localized image textures
(University of Missouri--Columbia, 2017)In the field of machine learning and pattern recognition, texture has been a prominent area of research. Humans are uniquely equipped to distinguish texture; however, computers are more equipped to automate the process. ... -
Multi-scale target detection based on morphological shared-weight neural network
(University of Missouri--Columbia, 2017)Convolutional Neural Networks (CNN) are a popular neural network structure for image based applications. This thesis discusses an alternative network, the morphological shared-weight neural network (MSNN) for object ... -
Recognition of sleep stages from sensor data
(University of Missouri--Columbia, 2015)Sleep is an essential activity for humans. It affects our physical and mental health. So monitoring sleep continuously can help detect any changes in sleep patterns that may be caused by sleep disorders or other diseases. ... -
Sleep stage classification using hydraulic bed sensor
(University of Missouri--Columbia, 2018)Sleep monitoring can help physicians diagnose and treat sleep disorders. Polysomnography(PSG) system is the most accurate and comprehensive method widely used in sleep labs to monitor sleep. However, it is expensive and ... -
A study of type-2 fuzzy clustering
(University of Missouri--Columbia, 2022)Fuzzy C-means (FCM) has been a prominent clustering algorithm for a long time. It was extended to a type-2 framework by the linguistic fuzzy C-means (LFCM) algorithm that operates on vectors of fuzzy numbers utilizing the ... -
Study on the improvement of the FCM algorithm based on evolutionary algorithms
(University of Missouri--Columbia, 2016)The Fuzzy C-Means (FCM) is a widely used clustering algorithm in unsupervised learning. It always converges to an optimum solution very quickly, thanks to its alternating optimization (AO) strategy. However, this AO strategy ... -
Target detection with morphological shared-weight neural network : different update approaches
(University of Missouri--Columbia, 2018)Neural networks are widely used for image processing. Of these, the convolutional neural network (CNN) is one of the most popular. However, the CNN needs a large amount of training data to improve its accuracy. If training ... -
A temporal analysis system for early detection of health changes
(University of Missouri--Columbia, 2014)To make it possible for elders to live independently at home and yet get help from health care providers when small changes in health conditions take place, smart home technologies are developed to enhance safety and monitor ... -
Textual summarization of data using linguistic protoform summaries
(University of Missouri--Columbia, 2015)With the unseen quantities of data being generated in all walks of life, varying from social media to health domain, introduction of new techniques in order to better understand this information content is imperative. ... -
Unstructured road detection in color imagery for the purpose of the automatic detection of explosive devices
(University of Missouri--Columbia, 2012)This thesis proposes a method for segmenting an unstructured dirt road in color space images using color and texture analysis. A support vector machine (SVM), or a Random Forest classifier is trained on samples of on and ... -
Vehicle detection using morphological shared-weight neural network in the multiple instance learning framework
(University of Missouri--Columbia, 2017)In this thesis, we design and implement an algorithm for object detection in aerial images based on the morphological shared-weight neural network (MSNN). The multiple instance learning (MIL) framework is used to avoid the ...