Index Catalog // ScholarsArchive@OSU

Data-Driven Approaches For Decoding Volitional Movement Intent From Bioelectrical Signals

Creator:: Cunha Dantas, Henrique
Abstract:: There are nearly two million limb amputees living in the United States of America. Loss of limbs results in profound changes in one's life. However, the underlying neural circuitry and much of the ability to sense and control movements of their missing limb is retained even after limb loss. This...
Resource Type:: Dissertation
Full Text:: Abstract approved: V John Mathews There are nearly two million limb amputees living in the United States

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
Full Text:: , John Warila, Yesh Godse, Ryan Batke, Fangzhou Yu, Andrew Sanders and Grace Stridick for working with

Fine-Grained Object Recognition Under Limited Training Data

Creator:: Lam, Michael Q.
Abstract:: This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
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

Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Creator:: Khorram, Saeed
Abstract:: In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
Resource Type:: Masters Thesis

Robust and Efficient Classification of Videos in the Wild

Creator:: Mahasseni, Behrooz
Abstract:: Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
Resource Type:: Dissertation

Interactive player tracking for videos in American football

Creator:: Bawaskar, Amit
Abstract:: This thesis presents an interactive software tool for tracking a moving object in a video. In particular, we focus on the problem of tracking a player in American football videos. Object tracking is one of the fundamental problems in computer vision. It is one of the most important components in...
Resource Type:: Masters Thesis

Statistical Properties and Guarantees for Certain Anomaly Detection Relevant Problems

Creator:: Liu, Si
Abstract:: Anomaly detection aims at detecting the points that appear different than the majority of the data, such that they are suspected to be generated from a different distribution. Anomaly detectors have been applied in many different fields, such as detecting fraudulent behaviors in bank transaction, finding broken sensors in a...
Resource Type:: Dissertation

Part-based and Uncertainty-Aware Few-shot Object Segmentation in Images

Creator:: Nguyen, Khoi D.
Abstract:: This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...
Resource Type:: Dissertation

Theory and Implementation of a Variational Database Management System

Creator:: Ataei, Parisa S.
Abstract:: In this thesis, I present the variational database management system, a formal framework and its implementation for representing variation in relational databases and managing variational information needs. A variational database is intended to support any kind of variation in a database. Specific kinds of variation in databases have already been...
Resource Type:: Dissertation

ScholarsArchive@OSU

Data-Driven Approaches For Decoding Volitional Movement Intent From Bioelectrical Signals

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

Fine-Grained Object Recognition Under Limited Training Data

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

Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Robust and Efficient Classification of Videos in the Wild

Interactive player tracking for videos in American football

Statistical Properties and Guarantees for Certain Anomaly Detection Relevant Problems

Part-based and Uncertainty-Aware Few-shot Object Segmentation in Images

Theory and Implementation of a Variational Database Management System

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