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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...
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...
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...
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...
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...
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...
Computer-aided tongue image diagnosis and analysis
(University of Missouri--Columbia, 2012)
This work focuses on computer-aided tongue image analysis, specifically, as it relates to Traditional Chinese Medicine (TCM). Computerized tongue diagnosis aid medical practitioners capture quantitative features to improve reliability...
Predicting stock price using sentiment analysis combining Twitter, search engine and investor intelligence data
(University of Missouri--Columbia, 2014)
in various economic and commercial indicators. In this project, daily sentiment features are generated from a Twitter dataset to build up a high accuracy prediction model for stock price movement. Google Search Queries and Investor Intelligence provide...
Physiological data analysis -- alcohol drinking prediction using statistical and deep learning methods
(University of Missouri--Columbia, 2017)
. The drinking record prediction pipeline is doing prediction based on oneminute record. The drinking episode pipeline is doing prediction based on thirty-minute episode. Statistical features are extracted from the thirty-minute data blocks. The drinking episode...
Data analytics in sports : improving the accuracy of NFL draft selection using supervised learning
(University of Missouri--Columbia, 2015)
increases the quality of the players in the league which would in turn increase revenue. However this is no easy task. The NFL prospect data sets are small and have varying feature set data which is difficult for machine learning algorithms to classify...
Three dimensional deformable image registration and registration verification
(University of Missouri--Columbia, 2015)
. We propose to apply well developed techniques in the computer vision field, including the feature/region/edge based detectors, descriptors and matching for deformable image registration and registration verification. Specifically, this thesis explores...
Statistical model-based methods for observation selection in wireless sensor networks and for feature selection in classification
(University of Missouri--Columbia, 2012)
-based approach. Finally We also apply the submodular mutual information-based selection method to feature selection for classification problems. We compare the proposed method with existing state-of-the-art attribute selection methods through extensive...
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 ...
Deep learning and DCT-based hand-crafted features for computer vision tasks
(University of Missouri--Columbia, 2022)
Feature extraction and matching are critical components for many computer vision tasks including camera pose estimation, 3D reconstruction, simultaneous localization and mapping (SLAM), and object tracking, etc. Features are image patterns that have...
Towards automated and explorative characterization of nano-energetic material response to directed energy
(University of Missouri--Columbia, 2023)
image features for characterizing reaction type. To perform the classification, we began with hand-crafted features and ensemble machine learning. Building on this, we modified a state-of-the-art transformer-based model for change detection to perform...
Conversation understanding and realistic artificial crash data generation with deep learning
(University of Missouri--Columbia, 2023)
these audio files and subsequently segmenting each conversation into customer and salesperson speaker turns to enable extraction of audio features and text embeddings for each speaker turn. In this dissertation we propose that a multimodal transformer network...
A framework for histopathology image segmentation and classification
(University of Missouri--Columbia, 2015)
breast cancer specimens. The first framework used handcrafted image features with a support vector machine classifier. The H and E stained images were first segmented into coherent partitions/superpixels; then a number of regional color and texture...
Deep learning methods for 360 monocular depth estimation and point cloud semantic segmentation
(University of Missouri--Columbia, 2022)
geometry-aware feature fusion mechanism that combines 3D geometric features with 2D image features. (ii) the self-attention-based transformer architecture to conduct a global aggregation of patch-wise information. (iii) an iterative depth refinement...
Tornado intensity prediction based on environment elements at tornado events starting points
(University of Missouri--Columbia, 2016)
predictability based on current atmospheric sensor networks, e.g., Doppler Radar. Environmental conditions at tornado start points may play a key role in determining the intensity; and therefore we explore the potential of using environment features as tornado...