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Now showing items 41-60 of 317
Probabilistic graphical models for protein structure prediction
(University of Missouri--Columbia, 2016)
Computationally predicting the folded and functional three-dimensional structure of a protein molecule from its amino acid sequence with high degree of accuracy is critically important in structural bioinformatics and has ...
Multi-scale target detection based on morphological shared-weight neural network
(University of Missouri--Columbia, 2017)
Convolutional Neural Networks (CNN) are a popular neural network structure for image based applications. This thesis discusses an alternative network, the morphological shared-weight neural network (MSNN) for object ...
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 ...
Machine-aided analysis of vote privacy using computationally complete symbolic attacker
(University of Missouri--Columbia, 2019)
Security protocols employ cryptographic primitives such as encryption and digital signatures to provide security guarantees of confidentiality and authenticity in the presence of malicious attackers. Due to the complexities ...
Deep learning based nuclei detection for quantitative histopathology image analysis
(University of Missouri--Columbia, 2016)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Quantitative analysis of histopathology images is important for both clinical purposes (e.g. to reduce/eliminate inter- and intra-observer variations ...
Distributed frequent hierarchical pattern mining for robust and efficient large-scale association discovery
(University of Missouri--Columbia, 2017)
Frequent pattern mining is a classic data mining technique, generally applicable to a wide range of application domains, and a mature area of research. The fundamental challenge arises from the combinatorial nature of ...
Permutation compression with applications to genomic data
(University of Missouri--Columbia, 2018)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] High Sequencing Technology generates data at an increasing rate. The technology is used widely in molecular biology. Technologies similar to this are ...
Relative depth estimation from single monocular images with deep convolutional network
(University of Missouri--Columbia, 2017)
Depth estimation from single monocular images is a theoretical challenge in computer vision as well as a computational challenge in practice. This thesis addresses the problem of depth estimation from single monocular ...
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 ...
Capturing and managing daily symptoms data in the treatment of autism spectrum disorder using mobile technology
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Autism Symptom Disorder (ASD) is a heterogeneous group of neurodevelopmental disorders characterized by difficulties with social interaction and ...
Selecting data for multilingual multi-domain neural machine translation on low resource languages
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] While machine translation has achieved impressive results on the world's most widely spoken languages, thousands of languages do not have the quantity ...
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 ...
Fuzzy-based conversational recommender for data-intensive science gateway applications
(University of Missouri--Columbia, 2018)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Neuro-scientists are increasingly relying on parallel and distributed computing resources for analysis and visualization of their neuron simulations. ...
Privacy preservation in mobile social networks
(University of Missouri--Columbia, 2019)
In this day and age with the prevalence of smartphones, networking has evolved in an intricate and complex way. With the help of a technology-driven society, the term "social networking" was created and came to mean using ...
Automatic geospatial content summarization and visibility enhancement by dehazing in aerial imagery
(University of Missouri--Columbia, 2017)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The objective of this work is to develop a methodology to summarize the content of a long sequential geospatial video using a few geospatial coverage ...
Lightweight IoT security middleware for end-to-end cloud-fog communication
(University of Missouri--Columbia, 2017)
IoT (Internet of Things) based smart devices such as sensors and wearables have been actively used in edge clouds i.e., 'fogs' to provide critical data during scenarios ranging from e.g., disaster response to in-home ...
In-memory distributed indexing for large-scale media data retrieval
(University of Missouri--Columbia, 2017)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Multimedia data includes various media types such as text, image and video. Recent research has shown that media data retrieval serves a critical role ...
Energy-aware mobile edge computing for low-latency visual data processing
(University of Missouri--Columbia, 2017)
New paradigms such as Mobile Edge Computing (MEC) are becoming feasible for use in e.g., real-time decision-making during disaster incident response to handle the data deluge occurring in the network edge. However, MEC ...
Spatial pyramid context-aware moving object detection and tracking for full motion video and wide aerial motion imagery /
(University of Missouri--Columbia, 2017)
A robust and fast automatic moving object detection and tracking system is essential to characterize target object and extract spatial and temporal information for different functionalities including video surveillance ...
Resdiue-residue contact driven protein structure prediction using optimization and machine learning
(University of Missouri--Columbia, 2017)
Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key ...