Index Catalog // ScholarsArchive@OSU

Probabilistic models for quality control in environmental sensor networks

Creator:: Dereszynski, Ethan W.
Abstract:: Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
Resource Type:: Dissertation

Protein secondary structure prediction using conditional random fields and profiles

Creator:: Shen, Rongkun
Abstract:: Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
Resource Type:: Masters Thesis
Full Text:: representation is the PSI-BLAST profile introduced by D. Jones, which is based on matching sequences of known

Image features and learning algorithms for biological, generic and social object recognition

Creator:: Zhang, Wei
Abstract:: Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
Resource Type:: Dissertation
Full Text:: . Viola and Jones (2001) employed rectangular Haar- like features for face detection and proposed a very

Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

Creator:: Zemicheal, Tadesse H.
Abstract:: Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
Resource Type:: Dissertation

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Creator:: Green, Kevin
Abstract:: Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
Resource Type:: Dissertation

Deep Learning for Human and Biological Languages

Creator:: Hong, Junki
Abstract:: We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Resource Type:: Dissertation

Deep Convolutional Network on Point Clouds for 3D Scene Understanding

Creator:: Wu, Wenxuan
Abstract:: As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
Resource Type:: Dissertation

Bayesian optimization with empirical constraints

Creator:: Azimi, Javad
Abstract:: Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
Resource Type:: Dissertation

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Action Segmentation with Limited Supervision

Creator:: Li, Jun
Abstract:: In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
Resource Type:: Dissertation

ScholarsArchive@OSU

Probabilistic models for quality control in environmental sensor networks

Protein secondary structure prediction using conditional random fields and profiles

Image features and learning algorithms for biological, generic and social object recognition

Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Deep Learning for Human and Biological Languages

Deep Convolutional Network on Point Clouds for 3D Scene Understanding

Bayesian optimization with empirical constraints

Semantic embodied navigation : developing agents that navigate from language and vision

Action Segmentation with Limited Supervision

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