Browsing by Author "Hougen, Dean"
Now showing items 1-20 of 47
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The Aesthetic Value of Videogames: An Analysis of Interactivity, Gameplay, & Player Performance
Jurgensen, Zachary (2018)In this dissertation, I set out to examine the artistic and aesthetic features of videogames as games. Ultimately, I argue that a complete understanding of the aesthetics of videogames requires a more robust account of the ... -
ANALYSIS OF SPACE, COGNITION AND PEDESTRIAN MOVEMENT
Zhang, Ying (2019-05)Understanding the movement of people in urban areas is one of the most significant issues on spatial science with a wide range of applications in urban design, public health, public safety and intelligent transportation ... -
Analysis of VANET Standard IEEE 1609.4 Mac Layer Multi-Channel Operations Using OMNeT++ and Veins
Rodriguez Coria, Susana A. (2018-12-14)VANETS is an ad hoc network in vehicles with wireless communication capability. The network utilizes a system to relay data from one vehicle to another vehicle or to a Road Side Unit (RSU). This communication is also known ... -
Application of deep learning to optimize computer-aided-detection and diagnosis of medical images
Maryada, Sai Kiran Reddy (2023-12-15)The field of medical imaging informatics has experienced significant advancements with the integration of artificial intelligence (AI), especially in tasks like detecting abnormalities in retinal fundus images. This ... -
Applied High-Order Singular Value Decomposition for Weight Compression and Expansion in Deep Neural Networks
Graham, Austin (2019-08)Complex deep learning objectives such as object detection and saliency, semantic segmentation, sequence-to-sequence translation, and others have given rise to training processes requiring increasing amounts of time and ... -
Automatic Machine Learning in Optimization and Data Augmentation
Dong, Xiaomeng (2022-05)This dissertation introduces Automatic Machine Learning (AutoML) as a potential approach to overcome current deep learning challenges on efficiency and cost. It also proposes two novel AutoML workflows to areas in deep ... -
Comparison of Machine Learning and Statistical Approaches for Predicting Travel Times in the Oklahoma Highway System
Saidi, Said Jalal (2020-12)Traffic management systems play a vital role in supporting the smooth flow of traffic in road networks. By accurately predicting travel time, a traffic condition parameter that is extensively used in such systems, we can ... -
The Context-Aware Learning Model
Suh, Joohee (2017-12)The ultimate goal of this research is to build a novel, generalized, arbitrary-depth, neural controller that performs reward- and experience-based neuromodulatory learning, which is online, bootstrapping, interactive, ... -
Deep Learning for Weak Target Detection in Range-Doppler Data
Dang, Bibi (2022-05)A consistent issue for detectors in radar systems is how to correctly distinguish target signals from random noise. This is especially true for weak targets with low signal-to-noise ratios (SNRs). Traditional target detection ... -
DESIGN AND DEVELOPMENT OF CARRIER ASSIGNMENT AND PACKET SCHEDULING IN LTE-A AND Wi-Fi
Narman, Husnu (2016-05-13)The highly competitive environment in today's wireless and cellular network industries is making the management of systems seek for better and more advance techniques to keep masses of data, complexity of systems and ... -
Designing Reliable Machine Learning Algorithms for Early Prediction of Preeclampsia
Bennett, Rachel (2021-08)Known as a pregnancy complication due to high blood pressure and may be accompanied by damage to another organ system, preeclampsia afflicts between 3 and 6 percent of US pregnancies each year. Studies have shown the ... -
Detection of Overshooting Cloud Tops with Convolutional Neural Networks
Kanneganti, Gowtham Teja (2020-05-08)Overshooting cloud tops can cause severe weather conditions, such as aviation turbulence, lightning, strong winds, heavy rainfall, hail, and tornadoes. Due to hazards caused by overshooting tops, several methods have been ... -
Developing and Applying Hybrid Deep Learning Models for Computer-Aided Diagnosis of Medical Image Data
Mudduluru, Sanjana (2023)The dissertation discusses three methods to address the challenges of applying deep learning models to medical imaging. The first method involves the development of a new joint deep learning model, J-Net, to achieve lesion ... -
Development of Deep Learning Methodologies for Modeling Navigational Features in Continuous Spaces
Hoyt, Zackary (2021-12)This thesis proposes generalized methodologies to model navigational features of continuous spaces using deep learning architectural approaches. Navigational features impact how an entity can effectively travel within a ... -
Efficient Neural Architecture Search using Genetic Algorithm
Morgan, Brandon (2022-08)NASNet and AmoebaNet are state-of-the-art neural architecture search systems that were able to achieve better accuracy than state-of-the-art human-made convolutional neural networks. Despite the innovation of the NASNet ... -
Evaluating GAM-Like Neural Network Architectures for Interpretable Machine Learning
Booker, William (2019-05)In many machine learning applications, interpretability is of the utmost importance. Artificial intelligence is proliferating, but before you entrust your finances, your well-being, or even your life to a machine, you’d ... -
Evolving Spiking Neural Networks with NEAT
Hirsch, Mary (2020)Spiking neural networks (SNNs) attempt to computationally model biological neurons. While similar to artificial neural networks (ANNs), SNNs preserve the temporal and binary aspects of neurons. Computational evolution is ... -
Forecasting landslide events in eastern Oklahoma and western Arkansas using empirical methods and statistical machine learning methods
Oyebanji, Oluwatobiloba (2022-12)Understanding the trend of landslide occurrence in eastern Oklahoma and western Arkansas is crucial to the human and social development of the region. Studies suggest rainfall is one of the major landslide triggering ... -
Graph Attention and Persistence for Traveling Salesman Problem
Aguilar Escamilla, Jose (2023-05-12)Combinatorial optimization problems have long been a computationally-challenging family of problems with high importance within science. Although algorithms to solve such problems exist, these classical/exact algorithms ... -
HiMean: A HyGene Approach to Semantic Analysis in a Medical Decision-Making Task
Martin, April (2014)This dissertation makes an exploratory comparison between two semantics models, Latent Semantic Analysis (LSA) and a newly introduced HiMean model based on the HyGene architecture, in a medical decision-making context. ...