• Automated vector-vector and vector-imagery geospatial conflation 

    Song, Wenbo (University of Missouri--Columbia, 2011)
    With the rapid advance of geospatial technologies, the availability of geospatial data from multiple sources has increased dramatically. Integration of multi-source geospatial data can provide insights and capabilities not ...
  • Estimation and tracking of elder activity levels for health event prediction 

    Harvey, Nicholas M. (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 

    Dale, Jeffrey (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 ...
  • Experimental study of random projections below the JL limit 

    Ye, Xiuyi (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 ...
  • Fractal Analysis of Seafloor Textures for Target Detection in Synthetic Aperture Sonar Imagery 

    Nabelek, Thomas R. (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, ...
  • Multi-scale target detection based on morphological shared-weight neural network 

    Shen, Shuxian (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 ...
  • A study of type-2 fuzzy clustering 

    Chantapakul, Watchanan (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 ...