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Applications of deep neural networks to protein structure prediction
(University of Missouri--Columbia, 2018)
Protein secondary structure, backbone torsion angle and other secondary structure features can provide useful information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity ...
Improving object recognition in aerial image and ambulatory assessment analysis by deep learning
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With the widespread usage of many different types of sensors in recent years, large amounts of diverse and complex sensor data have been generated and ...
New consensus-based algorithms for quality assessment in protein structure prediction
(University of Missouri--Columbia, 2010)
Two of the essential tasks in protein tertiary structure prediction are predicting quality and selecting the best quality model from given model structures. Finding solutions to these problems are fundamental to understanding ...
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 ...
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 ...
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 ...
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 ...