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Articles 1 - 7 of 7
Full-Text Articles in Engineering
Image-Based Roadway Assessment Using Convolutional Neural Networks, Weilian Song
Image-Based Roadway Assessment Using Convolutional Neural Networks, Weilian Song
Theses and Dissertations--Computer Science
Road crashes are one of the main causes of death in the United States. To reduce the number of accidents, roadway assessment programs take a proactive approach, collecting data and identifying high-risk roads before crashes occur. However, the cost of data acquisition and manual annotation has restricted the effect of these programs. In this thesis, we propose methods to automate the task of roadway safety assessment using deep learning. Specifically, we trained convolutional neural networks on publicly available roadway images to predict safety-related metrics: the star rating score and free-flow speed. Inference speeds for our methods are mere milliseconds, enabling …
Metadata-Based Image Collecting And Databasing For Sharing And Analysis, Xi Wu
Metadata-Based Image Collecting And Databasing For Sharing And Analysis, Xi Wu
Theses and Dissertations--Computer Science
Data collecting and preparing is generally considered a crucial process in data science projects. Especially for image data, adding semantic attributes when preparing image data provides much more insights for data scientists. In this project, we aim to implement a general-purpose central image data repository that allows image researchers to collect data with semantic properties as well as data query. One of our researchers has come up with the specific challenge of collecting images with weight data of infants in least developed countries with limited internet access. The rationale is to predict infant weights based on image data by applying …
Depth Enhancement And Surface Reconstruction With Rgb/D Sequence, Xinxin Zuo
Depth Enhancement And Surface Reconstruction With Rgb/D Sequence, Xinxin Zuo
Theses and Dissertations--Computer Science
Surface reconstruction and 3D modeling is a challenging task, which has been explored for decades by the computer vision, computer graphics, and machine learning communities. It is fundamental to many applications such as robot navigation, animation and scene understanding, industrial control and medical diagnosis. In this dissertation, I take advantage of the consumer depth sensors for surface reconstruction. Considering its limited performance on capturing detailed surface geometry, a depth enhancement approach is proposed in the first place to recovery small and rich geometric details with captured depth and color sequence. In addition to enhancing its spatial resolution, I present a …
A Diverse Band-Aware Dynamic Spectrum Access Architecture For Connectivity In Rural Communities, Vijay K. Shah
A Diverse Band-Aware Dynamic Spectrum Access Architecture For Connectivity In Rural Communities, Vijay K. Shah
Theses and Dissertations--Computer Science
Ubiquitous connectivity plays an important role in improving the quality of life in terms of economic development, health and well being, social justice and equity, as well as in providing new educational opportunities. However, rural communities which account for 46% of the world's population lacks access to proper connectivity to avail such societal benefits, creating a huge "digital divide" between the urban and rural areas. A primary reason is that the Information and Communication Technologies (ICT) providers have less incentives to invest in rural areas due to lack of promising revenue returns. Existing research and industrial attempts in providing connectivity …
Novel Applications Of Machine Learning In Bioinformatics, Yi Zhang
Novel Applications Of Machine Learning In Bioinformatics, Yi Zhang
Theses and Dissertations--Computer Science
Technological advances in next-generation sequencing and biomedical imaging have led to a rapid increase in biomedical data dimension and acquisition rate, which is challenging the conventional data analysis strategies. Modern machine learning techniques promise to leverage large data sets for finding hidden patterns within them, and for making accurate predictions. This dissertation aims to design novel machine learning-based models to transform biomedical big data into valuable biological insights. The research presented in this dissertation focuses on three bioinformatics domains: splice junction classification, gene regulatory network reconstruction, and lesion detection in mammograms.
A critical step in defining gene structures and mRNA …
Automated Network Security With Exceptions Using Sdn, Sergio A. Rivera Polanco
Automated Network Security With Exceptions Using Sdn, Sergio A. Rivera Polanco
Theses and Dissertations--Computer Science
Campus networks have recently experienced a proliferation of devices ranging from personal use devices (e.g. smartphones, laptops, tablets), to special-purpose network equipment (e.g. firewalls, network address translation boxes, network caches, load balancers, virtual private network servers, and authentication servers), as well as special-purpose systems (badge readers, IP phones, cameras, location trackers, etc.). To establish directives and regulations regarding the ways in which these heterogeneous systems are allowed to interact with each other and the network infrastructure, organizations typically appoint policy writing committees (PWCs) to create acceptable use policy (AUP) documents describing the rules and behavioral guidelines that all campus network …
Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal
Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal
Theses and Dissertations--Computer Science
Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …