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Classification of twitter trends using feature ranking and forward feature selection
(University of Missouri--Columbia, 2015)
, we attempt to solve this challenge using various machine learning techniques. This thesis includes a new approach for classifying Twitter trends by adding a layer of feature selection and feature ranking. A variety of feature ranking algorithms...
Integration Features in the Development of Software Product Line Architecture
(2015-08-12)
, the difficulty of relating product line features to PLA, and the overhead of manually creating and maintaining variation points in PLA. The approach is implemented and integrated in ArchStudio, an Eclipse-based architecture development toolset. The developed tool...
A flexible speech feature converter based on an enhanced architecture of U-net
(University of Missouri--Columbia, 2020)
In order to analyze speech or audio, many methods are applied to transform the time domain signals into various features such as the mel spectral features and WORLD vocoder features. These two types of features can both be extracted from speech...
Acoustic feature-based sentiment analysis of call center data
(University of Missouri--Columbia, 2017)
. A typical approach is to find a set of acoustic features from audio data that can indicate or predict a customer's attitude, opinion, or emotion state. For audio signals, acoustic features have been widely used in many machine learning applications...
Face verification using high dimensional feature
(University of Missouri--Columbia, 2014)
Estimation of crop residue cover in high-resolution RGB images using features from a pre-trained convolutional neural network
(University of Missouri--Columbia, 2022)
,400 ROI images; 3,000 used for cross validation and training (data collected in 2018) and 1,400 used for testing (data collected in 2019). The percent residue for each ROI image (ground truth) was determined by a bullseye grid method (n = 100). Features...
iHear – Lightweight Machine Learning Engine with Context Aware Audio Recognition Model
(University of Missouri–Kansas City, 2016)
With the increasing popularity and affordability of smartphones, there is a high demand to add
machine-learning engines to smartphones. However, Machine Learning with smartphones is typically
not feasible due to the heavy ...
Supervised learning methods for hand-held ground penetrating radar
(University of Missouri--Columbia, 2016)
, computational methods for detecting dangerous targets in GPR data are explored. First, an anomaly detection algorithm which can act as a prescreener is described. Then, two feature extraction methods are implemented in order to extract relevant features from...
Subsurface explosive hazard detection using MIMO forward-looking ground penetrating radar
(University of Missouri--Columbia, 2015)
locations. Alarm locations have log-Gabor statistical features and spectral features, among others, extracted from multiple polarizations. The ability of these features to reduce the number of false alarms and increase the probability of detection...
Confocal microscopy imaging analysis of plant morphodynamics
(University of Missouri--Columbia, 2010)
. Key features may then be identified and an abstracted version of the image may be generated. Next, motion analysis may be performed on the structures within the pollen tube. Six methods of point feature detection algorithms are discussed...
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 targets of interest...
The histogram of partitioned localized image textures
(University of Missouri--Columbia, 2017)
this by taking images and extracting meaningful features that describe their texture. Some of these features are the Haralick texture features, local binary pattern (LBP), and the local direction pattern (LDP). Using the local directional pattern as an example...
Feature-based Analysis for Open Source using Big Data Analytics
(2015)
The open source code base has increased enormously and hence understanding the functionality of the projects has become extremely difficult. The existing approaches of feature discovery that aim to identify functionality are typically semi...
Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics
(2015)
the code and build an accurate model that represents the software system of the open source.
The objective of this thesis is to provide a solution to this problem by building a framework that can extract the features, identify components, connectors from...
The enigmatic thirteen micron feature
(University of Missouri--Columbia, 2013)
from which we observe several interesting spectral features. The observed AGB star spectra have been classified according to their shapes and wavelength positions of the dust features. Alongside the main spectral features around 8-12μm...
Extracting extremal features from 3D volume data
(University of Missouri--Columbia, 2014)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Extremal features are implicit curve, surface and points features defined on 3D data with a scalar field and a tensor field. The extremal curves, surfaces and points are the set...
Using infrared observations of circumstellar dust around evolved stars to test dust formation hypothesis
(University of Missouri--Columbia, 2011)
understanding of the contribution of dust to many aspects of astrophysics. This thesis aims to study how the mineralogy and morphology of circumstellar dust varies with the pulsation cycle of the star and how the variation in spectral dust features (temporally...
Remembering complex objects in visual working memory
(University of Missouri--Columbia, 2013)
include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli which possessed multiple features per stimulus item. Some past research that used the same methodology as our...
A green residential wish list : most important features according to homeowners
(University of Missouri--Columbia, 2012)
' green features. Despite of works in environmental valuation of residences that possess those features, studies dealing with attitudes and behaviors towards green products have mostly focused on non-durable products or on energy-efficient appliances...
Local and deep texture features for classification of natural and biomedical images
(University of Missouri--Columbia, 2019)
Developing efficient feature descriptors is very important in many computer vision applications including biomedical image analysis. In the past two decades and before the popularity of deep learning approaches in image classification, texture...