Search Constraints

Start Over
Filtering by: Creator Castellano, Michael A. Remove constraint Creator: Castellano, Michael A. Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan

Search Results

  • Object detection in biological images using a search-based framework

    Creator:
    Lam, Michael
    Abstract:
    This thesis addresses a basic problem in computer vision, that of semantic labeling of images. Our work is aimed at object detection in biological images for evolutionary biology research. In particular, our goal is to detect nematocysts in Scanning Electron Microscope (SEM) images. This biological domain presents challenges for existing...
    Resource Type:
    Masters Thesis
    Full Text:
    Framework by Michael Lam A THESIS submitted to Oregon State University in partial

  • Analysis of bio-based composites for image segmentation with the aid of games

    Creator:
    Inouye, Jennifer A.
    Abstract:
    A fundamental problem in computer vision is to partition an image into meaningful segments. While image segmentation is required by many applications, the thesis focuses on segmentation of computed tomography (CT) images for analysis and quality control of composite materials. The key research contribution of this thesis is a novel...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Jennifer A. Inouye for the degree of Master of Science of Computer

  • A tool for visualizing sequence alignments and associating annotations

    Creator:
    Zhang, Wenpeng
    Abstract:
    Alignment of genomic sequences from different species is becoming an increasingly powerful method in biology, and is being used for many purposes. The result of sequence alignments is a list of pairs of matched locations between the pattern string and the text string. However, without any proper visualization tools to...
    Resource Type:
    Capstone Project
    Full Text:
    A Tool for Visualizing Sequence Alignments and Associating

  • Learning MDP action models via discrete mixture trees

    Creator:
    Wynkoop, Michael S.
    Abstract:
    This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
    Resource Type:
    Masters Thesis
    Full Text:
    Trees by Michael S. Wynkoop A THESIS submitted to Oregon State University in partial fulfillment

  • 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
    Full Text:
    All Rights Reserved Fine-Grained Object Recognition Under Limited Training Data by Michael Lam A

  • Action Selection for Heterologous Control of a Continuous-Output Myoelectric Prosthesis

    Creator:
    Sylwester, Sean T.
    Abstract:
    Significance: Movement intent decoding algorithms can interpret human bioelectrical signals to control prosthetic limbs with many degrees of freedom (DOFs). This work involves decoding volitional movement intent from surface electromyogram (sEMG) signals to control prosthetic arms. To train these algorithms, patients flex their muscles to “follow” a movement prompt, and...
    Resource Type:
    Masters Thesis
    Full Text:
    : Action Selection for Heterologous Control of a Continuous-Output Myoelectric Prosthesis Abstract

  • Decentralized Multi-Robot Exploration with Sparse Communication through Deep Imitation Learning

    Creator:
    Senewiratne, Yomal K.
    Abstract:
    We present a method for decentralized, multi-robot exploration in adverse environments where communication is minimal. A key conceptual feature of our method is enabling implicit coordination between robots by training a Convolutional Neural Network (CNN) as a heuristic for planning using Monte Carlo Tree Search (MCTS). Our method consists of...
    Resource Type:
    Masters Thesis
    Full Text:
    approved: Geoffrey A. Hollinger We present a method for decentralized, multi-robot exploration in adverse

  • Behavior graphs for data-driven animation of 3d characters

    Creator:
    Srinivasan, Madhusudhanan
    Abstract:
    In this dissertation, we present a user-in-the-loop method for the design of an interactive motion data structure that benefits from the advantages of both motion graphs and blend-based techniques. Our novel approach automatically analyzes a traditional motion graph built from labeled motion clips. The result is a more condensed, coarser...
    Resource Type:
    Dissertation
    Full Text:
    : Behavior Graphs for Data-driven Animation of 3D Characters Abstract approved: Ronald A. Metoyer In this

  • From shape-based object recognition and discovery to 3D scene interpretation

    Creator:
    Payet, Nadia
    Abstract:
    This dissertation addresses a number of inter-related and fundamental problems in computer vision. Specifically, we address object discovery, recognition, segmentation, and 3D pose estimation in images, as well as 3D scene reconstruction and scene interpretation. The key ideas behind our approaches include using shape as a basic object feature, and...
    Resource Type:
    Dissertation
    Full Text:
    addresses a number of inter-related and fundamental problems in com- puter vision. Specifically, we address

  • 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
    Full Text:
    image pixel with a class of the object occupying that pixel, where the class may represent a semantic