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Filtering by: Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan Committee Member Li, Fuxin Remove constraint Committee Member: Li, Fuxin

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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
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
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
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
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
Counterfactual States for Atari Agents via Generative Deep Learning

Creator:

Olson, Matthew L.

Abstract:

Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...

Resource Type:

Masters Thesis
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
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
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

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Academic Affiliation

Electrical Engineering and Computer Science9

Advisor

Todorovic, Sinisa5
Dietterich, Thomas G.1
Lee, Stefan1
Mathews, V. John1
Wong, Weng Keen1

Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 2017 to 2024

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Committee Member

Fern, Alan[remove]9
Li, Fuxin[remove]9
Rosulek, Mike2
Tyler, Brett2
Bolte, John1
more Committee Members »

Creator

Cunha Dantas, Henrique1
Krantz, Jacob1
Lam, Michael Q.1
Li, Jun1
Mahasseni, Behrooz1
more Creators »

Contributor

Li, Fuxin1
Neal, Lawrence1
Wong, Weng Keen1

Date

Date range begin – Date range end

Current results range from 2016 to 2023

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Decade

2020-20294
2010-20195

Degree Field

Computer Science8
Electrical and Computer Engineering1

Degree Level

Doctoral7
Master's2

Degree Name

Doctor of Philosophy (Ph.D.)7
Master of Science (M.S.)2

Language

English [eng]9

License

All rights reserved9

Non-Academic Affiliation

Oregon State University. Graduate School1

Peer Reviewed

No8

Resource Type

Dissertation7
Masters Thesis2

Rights Statement

In Copyright9

Subject

Computer multitasking1
Computer vision1
Human body in motion pictures1
Human locomotion1
Machine learning1
more Subjects »

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