Browsing OU - Theses by Author "Fagg, Andrew"
Now showing items 1-12 of 12
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Automated Detection of Bird Roosts Using NEXRAD Radar Data and Convolutional Neural Networks
Chilson, Carmen (2017-12-15)NEXRAD radars have proven to be an effective tool for detecting bird roosts for several species or birds, however manually locating these roosts in radar images is a time consuming process. We introduce a Convolutional ... -
Automated Location of Bird Roosts Using NEXRAD Data and Image Segmentation
Avery, Katherine (2020)Weather surveillance radars can effectively detect flying animals, such as groups of birds, bats, and insects. Further, these radars are demonstrably useful for detecting the existence of certain bird roosting locations, ... -
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 ... -
A Constraint Driven Approach to Neural and Muscle Recruitment in Wrist Motor Tasks
Lopez - Santillana, Manuel (2020-07-30)The transformation from visual stimulus to muscle recruitment is a non- linear one: it must take into account the configuration of the body and the lines of action of the muscles. The primary cortex plays a role in the ... -
Correction of Kinematic Data from a Self-Initiated Prone Position Crawler Trainer for Infants with Cerebral Palsy
Wilson, Leonard Jr (2017-12)In recent years small, inexpensive inertial measurement units (IMUs) have been used clinically to monitor human body joint angles in order to assess the progression of, or recovery from, various diseases affecting movement, ... -
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 ... -
Focal Vibration for Upper Limb Rehabilitation After Stroke
Duginski, Grace (2022-05-13)Stroke is the fifth leading cause of death and a leading cause of disability in the state of Oklahoma and the United States. Although there are several approaches to stroke rehabilitation, most stroke survivors live with ... -
Indoor Localization and Mapping Using Deep Learning Networks
Soni, Ravi (2017)Over the past several decades, robots have been used extensively in environments that pose high risk to human operators and in jobs that are repetitive and monotonous. In recent years, robot autonomy has been exploited to ... -
Integrated 3D Printing of Robotic Structures and Circuits
McDonough, Sean (2016-12)Advances in upper limb prostheses have lowered the cost of prosthetic limbs, enabling access for a larger population of amputees. Other advancements, such as robotic prosthetics, enable amputees to more easily grasp ... -
Real-Time Gesture Recognition with Mini Drones
Davis, Taner (2018-12-14)Drones are being used worldwide to perform many functions - medical deliveries, video recording, and surveying to name a few. Their growing presence is paralleled by the growing world of Machine Learning (ML). This thesis ... -
Thyroid nodule ultrasound image analysis and feature extraction
Dong, Xiaomeng (2018-05-11)In this study, I introduce a novel workflow for extracting useful features in thyroid ultrasound images using deep learning and machine learning methods. The methodology combines Convolutional Auto-Encoder, Local Binary ... -
Using Novelty Seeking Reward Evolution Strategies to Train Generative Adversarial Networks
Jabr, Khaled (2018-12-14)Generative Adversarial Networks (GANs) are a subclass of deep generative models that aim to implicitly learn to model a data distribution. While GANs have gained wide research attention, and achieved much success, when ...