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  • Calibrating the highway safety manual predictive methods for Oregon rural state highways

    Creator:
    Xie, Fei
    Abstract:
    The first edition of the Highway Safety Manual (HSM) provides a quantitative approach to predict the safety of transportation facilities based on the recently developed scientific methods. This approach, known as the predictive method, was developed for several states in the United States. Due to differences in driver population, weather...
    Resource Type:
    Masters Thesis
    Full Text:
    A THESIS submitted to Oregon State University in partial fulfillment of the requirement

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation
    Full Text:
    Oregon State University in partial fulfillment of the requirements for the degree of Doctor of

  • Re-understanding Finite-State Representations of Recurrent Policy Networks

    Creator:
    Danesh, Mohamad H.
    Abstract:
    We propose an approach for understanding control policies represented as recurrent neural networks. Recent work has approached this problem by transforming such recurrent policy networks into finite-state machines (FSM) and then analyzing the equivalent minimized FSM. While this led to interesting insights, the minimization process can obscure a deeper understanding...
    Resource Type:
    Masters Thesis
    Full Text:
    become part of the permanent collection of Oregon State University libraries. My signature below

  • 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
    Full Text:
    to Oregon State University in partial fulfillment of the requirements for the degree of Doctor

  • Efficient Incremental Panorama Reconstruction from Multiple Videos

    Creator:
    Feng, Zhongyuan
    Abstract:
    Constructing a panorama from a set of videos is a long-standing problem in computer vision. A panorama represents an enhanced still-image representation of an entire scene captured in a set of videos, where each video shows only a part of the scene. Importantly, a panorama shows only the scene background,...
    Resource Type:
    Capstone Project
    Full Text:
    : Major Professor, representing Computer Science Director of the Oregon State University of Electrical

  • Variant Annotation

    Creator:
    He, Jun
    Abstract:
    With the development of technologies in genome sequencing and variant detection, a huge number of variants are detected. To further analyze the variants, it requires an efficient tool to annotate the functional effect of variants. This project managed to develop an efficient program to annotate the functional effect of variants...
    Resource Type:
    Capstone Project
    Full Text:
    the permanent collection of Oregon State University libraries. My signature below authorizes release

  • Novelty Detection Under the Multi-Instance Multi-Label Framework

    Creator:
    Lou, Qi
    Abstract:
    Novelty detection plays an important role in machine learning and signal processing. This project studies novelty detection in a new setting where the data object is represented as a bag of instances and associated with multiple class labels, referred to as multi-instance multi-label (MIML) learning. Contrary to the common assumption...
    Resource Type:
    Capstone Project
    Full Text:
    Framework by Qi Lou A PROJECT REPORT submitted to Oregon State University in partial fulfillment of

  • Web-PST : Web-based Pesticide Screening Tool

    Creator:
    Manda, Ashwin Prasad
    Abstract:
    We have developed a web-based software tool for evaluating the potential risk of pesticides on the surrounding environment. The software tool is called Web-based Pesticide Screening Tool (Web-PST). It uses the formulas and standards specified by the Soil/Pesticide Interaction Screening Procedure Version II (SPISP II). Web-PST closely models the stand-alone...
    Resource Type:
    Capstone Project
    Full Text:
    Computer Science Oregon State University Corvallis, OR 97331 October 17th 2002 Major Professor: Dr

  • WebRUSLE : web-based revised universal soil loss equation (RUSLE)

    Creator:
    Wuttiwat, Teerawat
    Abstract:
    Revised Universal Soil Loss Equation (RUSLE) is a standard for estimating soil loss caused by rainfall and overland flow. The current software tool that implements this standard is RUSLE 1.06b, which is a stand-alone DOS application. In this project, we converted the DOS application to a Web application, which we...
    Resource Type:
    Capstone Project
    Full Text:
    Member: Dr. Jeffrey Steiner Dept. of Computer Science Oregon State University Corvallis, OR 97331

  • A collaborative filtering algorithm and evaluation metric that accurately model the user experience

    Creator:
    McLaughlin, Matthew
    Abstract:
    "Collaborative filtering algorithms’ performances have been evaluated using a variety of metrics. These metrics, such as Mean Absolute Error and Precision, have often ignored recommendations for which they do not have data. Ignoring these recommendations has provided numbers which do not accurately represent the user experience. Qualitatively we have seen...
    Resource Type:
    Capstone Project
    Full Text:
    filtering system with "dead data". University of Minnesota TR 98-017. 3. Herlocker, J. L., Konstan, J