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Filtering by: Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Committee Member Li, Fuxin Remove constraint Committee Member: Li, Fuxin Degree Level Doctoral Remove constraint Degree Level: Doctoral Language English [eng] Remove constraint Language: English [eng]

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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...

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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...

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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
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...

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Dissertation
Object Tracking-by-Segmentation in Videos

Creator:

Chen, Sheng

Abstract:

This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...

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Dissertation

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Academic Affiliation

Electrical Engineering and Computer Science5

Advisor

Fern, Alan2
Burnett, Margaret M.1
Dietterich, Thomas G.1
Lee, Stefan1
Todorovic, Sinisa1

Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 2017 to 2024

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Committee Member

Li, Fuxin[remove]5
Tadepalli, Prasad[remove]5
Bae, Harold1
Fern, Alan1
Fern, Xiaoli1
more Committee Members »

Creator

Aziere, Nicolas1
Chen, Sheng1
Dodge, Jonathan E.1
Koul, Anurag1
Krantz, Jacob1

Date

Date range begin – Date range end

Current results range from 2017 to 2024

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Decade

2020-20294
2010-20191

Degree Field

Computer Science5

Degree Level

Doctoral[remove]5

Degree Name

Doctor of Philosophy (Ph.D.)5

File Format

pdf1

Language

English [eng][remove]5

License

All rights reserved5

Non-Academic Affiliation

Oregon State University. Graduate School1

Peer Reviewed

No5

Resource Type

Dissertation5

Rights Statement

In Copyright5

Subject

Image processing1
Image segmentation1
Neural networks (Computer science)1
Video recordings1

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