Index Catalog // ScholarsArchive@OSU

Ideal Thumbnail-Preserving Encryption for Balancing Image Privacy and Usability

Creator:: Tajik, Kimia
Abstract:: In this dissertation, we propose Ideal Thumbnail-Preserving Encryption (Ideal TPE), as a special case of format-preserving encryption, to balance image privacy and usability concerns in a cloud environment. We first introduce a concrete construction for Ideal TPE, that provably leaks nothing about the plaintext (unencrypted) image beyond its thumbnail. We...
Resource Type:: Dissertation
Full Text:: rigor, whereas ideal TPE provides an understandable cryptographic security guarantee. Face De

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
Full Text:: computing and independent critical thinking. Paul De Palma, your infectious spirit sparked my love for

Regularization-Based Data Integration and Its Application to Genome-Wide Association Studies

Creator:: Li, Kai
Abstract:: In genome-wide association studies, it is often challenging to have consistent findings from independent studies. This "lack of reproducibility" issue is partially caused by the relatively small sample size compared to the number of genetic markers in every single study. Therefore, researchers have developed statistical methods to integrate multiple studies...
Resource Type:: Dissertation

Image Based Crypto

Creator:: Basa, Gungor
Abstract:: The ability to create reproducible cryptographically secure keys from temporal environments (e.g., images) has the potential to be a contributor to effective cryptographic mechanisms. Due to the noisy nature of these environments, achieving this goal in a user friendly fashion is a very challenging task, especially since there exists a...
Resource Type:: Masters Thesis

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

Creator:: Aziere, Nicolas
Abstract:: This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Resource Type:: Dissertation

A Deep Action Segmentation and Its Explanation with a Dictionary of Meaningful Attention Maps

Creator:: Trigkakis, Dimitrios
Abstract:: This thesis addresses the problem of temporal action segmentation in videos, where the goal is to label every video frame with the appropriate action class present. We focus on the domain of NFL football videos, where action classes represent common football play types. For action segmentation, we use a temporal...
Resource Type:: Masters Thesis
Full Text:: earliest works to appear towards 8 this goal [20] used de-convolutional networks that were appended to

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

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Creator:: Koul, Anurag
Abstract:: Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
Resource Type:: Dissertation

Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

Creator:: Lei, Peng
Abstract:: This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
Resource Type:: Dissertation

Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

Creator:: Dodge, Jonathan E.
Abstract:: Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
Resource Type:: Dissertation

ScholarsArchive@OSU

Ideal Thumbnail-Preserving Encryption for Balancing Image Privacy and Usability

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

Regularization-Based Data Integration and Its Application to Genome-Wide Association Studies

Image Based Crypto

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

A Deep Action Segmentation and Its Explanation with a Dictionary of Meaningful Attention Maps

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

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

Limit your search

Academic Affiliation

Advisor

Commencement Year

Committee Member

Creator

Contributor

Date

Decade

Degree Field

Degree Level

Degree Name

File Format

Language

License

Non-Academic Affiliation

Peer Reviewed

Resource Type

Rights Statement

Subject

Search Constraints

Search Results

Limit your search