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Now showing items 21-40 of 40
Data-driven 3D shape modeling
(University of Missouri--Columbia, 2010)
3D shape modeling is essential for computer to understand our real world. So far, 3D shaping modeling is still an open issue. There are too much raw data around, but there is no uniform or standard way to translate them for computers. My work...
Volumetric medical image segmentation with deep learning pipelines
(University of Missouri--Columbia, 2020)
Automated semantic segmentation in the domain of medical imaging can enable a faster, more reliable, and more affordable clinical workflow. Fully convolutional networks (FCNs) have been heavily used in this area due to the ...
3D city scale reconstruction using wide area motion imagery
(University of Missouri--Columbia, 2018)
3D reconstruction is one of the most challenging but also most necessary part of computer vision. It is generally applied everywhere, from remote sensing to medical imaging and multimedia. Wide Area Motion Imagery is a ...
Reliable service chain orchestration for scalable data-intensive computing at infrastructure edges
(University of Missouri--Columbia, 2019)
In the event of natural or man-made disasters, geospatial video analytics is valuable to provide situational awareness that can be extremely helpful for first responders. However, geospatial video analytics demands massive ...
Statistical inference in wireless sensor and mobile networks
(University of Missouri--Columbia, 2010)
In recent years, wireless sensor networks have emerged as a cost effective alternative to traditional wired sensor systems. In the meantime, mobile networks have also gained many momentums. The two emerging networks share ...
Estimation of dynamic detector confidence thresholds in SAS imagery using mixture models
(University of Missouri--Columbia, 2019)
As machine learning has matured over the years, more and more safety critical tasks have been entrusted to computers. Automated target recognition (ATR), the problem of identifying explosive hazards on the sea?oor, is one ...
Out-of-core image techniques with extensions for WAMI
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Out-of-core image techniques provide for interactive visualization, analysis, and processing of extremely large images exceeding primary memory. This ...
Deepnet : an extensible data acquisition and curation framework supporting computer vision deep learning research
(University of Missouri--Columbia, 2018)
We present a system, DeepNet, for ingestion, curation, and management of geospatial data images to facilitate a range of geospatial research. The system allows for the semi-autonomous ingestion of geospatial data from a ...
AMD, analysis of mood dysregulation : a machine learning approach
(University of Missouri--Columbia, 2016)
There is a popular saying, "Stress kills." This statement can be true with repeated exposures to psychological mood dysregulation, which can lead to or worsen stress related conditions such as heart disease and cancer. ...
Deep learning for small object detection in images
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With the rapid development of deep learning in computer vision, especially deep convolutional neural networks (CNNs), significant advances have been ...
KOLAM : human computer interfaces fro visual analytics in big data imagery
(University of Missouri--Columbia, 2018)
In the present day, we are faced with a deluge of disparate and dynamic information from multiple heterogeneous sources. Among these are the big data imagery datasets that are rapidly being generated via mature acquisition ...
Image matching and image super-resolution via deep learning
(University of Missouri--Columbia, 2018)
The advancement of 3D depth sensors, such as LIDAR (Light Detection And Ranging) scanners, has provided an effective alternative to traditional CAD-based and image-based approaches for 3D modeling. The output of the 3D ...
Significance linked connected component analysis plus
(University of Missouri--Columbia, 2018)
An image coding algorithm, SLCCA Plus, is introduced in this dissertation. SLCCA Plus is a wavelet-based subband coding method. In wavelet-based subband coding, the input images will go through a wavelet transform and be ...
Region based object detectors for recognizing birds in aerial images
(University of Missouri--Columbia, 2019)
This project explores different types of deep neural networks (DNNs) for recognizing birds in aerial images based on real data provided by the Missouri Department of Conservation. The pipeline to identify birds from an ...
The study of privacy issues in the use of cloud storage
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Cloud Computing has become increasingly popular with both consumers and businesses. Consumers use cloud provider offerings to store files, share content ...
Revealing the conformation and properties of human genome, protein molecules and protein domain co-occurrence network
(University of Missouri--Columbia, 2012)
Deoxyribonucleic acid, or DNA, encodes genetic instructions for the functionalities of organisms. For human beings, 23 pairs of chromosomes, containing DNA strands, form a globule structure in the nucleus. This chromosomal ...
Computational protein structure prediction using deep learning
(University of Missouri--Columbia, 2020)
Protein structure prediction is of great importance in bioinformatics and computational biology. Over the past 30 years, many machine learning methods have been developed for this problem in homology-based and ab-initio ...
Multi-stage cloud framework based on agents for dynamic, scalable, and secure distributed computing
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] We have reached the point of ubiquitous sensing as we continue to witness the explosive growth of the Internet of Things (IoT) and other ...
Improving protein structure prediction by deep learning and computational optimization
(University of Missouri--Columbia, 2019)
Protein structure prediction is one of the most important scientific problems in the field of bioinformatics and computational biology. The availability of protein three-dimensional (3D) structure is crucial for studying ...
User experience and robustness in social virtual reality applications
(University of Missouri--Columbia, 2020)
Cloud-based applications that rely on emerging technologies such as social virtual reality are increasingly being deployed at high-scale in e.g., remote-learning, public safety, and healthcare. These applications increasingly ...