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Filtering by: Creator Webb, Jonathan K. Remove constraint Creator: Webb, Jonathan K. Subject Machine learning Remove constraint Subject: Machine learning

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  • Improving robotic grasping performance using machine learning techniques

    Creator:
    Goins, Alex Keith
    Abstract:
    Robots are being utilized in ever more complex tasks and environments to help humans with difficult or dangerous tasks. However, robotic grasping is still in its infancy and is one of the limiting factors which prevent the deployment of robots in the home and other assisted living scenarios. Traditional methods...
    Resource Type:
    Masters Thesis
    Full Text:
    distribution over functions f(x). In our work, each data instance xi is a grasp, which has k features that

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    TaskPredictor for FA as a function of the number of selected features K. Error bars denote 95% confidence

  • Combining coordination mechanisms to improve performance in multi-robot teams

    Creator:
    Nasroullahi, Ehsan
    Abstract:
    Coordination is essential to achieving good performance in cooperative multiagent systems. To date, most work has focused on either implicit or explicit coordination mechanisms, while relatively little work has focused on the benefits of combining these two approaches. In this work we demonstrate that combining explicit and implicit mechanisms can...
    Resource Type:
    Masters Thesis

  • Toward harnessing user feedback for machine learning

    Creator:
    Stumpf, Simone, Rajaram, Vidya, Li, Lida, Burnett, Margaret, 1949-, Dietterich, Thomas Glen, Sullivan, Erin, Drummond, Russell, and Herlocker, Jonathan Lee
    Abstract:
    There has been little research into how end users might be able to communicate advice to machine learning systems. If this resource--the users themselves--could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved and the users' understanding and trust of the system could improve...
    Resource Type:
    Technical Report
    Full Text:
    Drummond, Jonathan Herlocker Oregon State University School of Electrical Engineering and Computer

  • Interacting meaningfully with machine learning systems : three experiments

    Creator:
    Oregon State University. Dept. of Computer Science, Stumpf, Simone, Rajaram, Vidya, Li, Lida, Wong, Weng-Keen, Burnett, Margaret, 1949-, Dietterich, Thomas Glen, Sullivan, Erin, and Herlocker, Jonathan Lee
    Abstract:
    Although machine learning is becoming commonly used in today's software, there has been little research into how end users might interact with machine learning systems, beyond communicating simple "right/wrong" judgments. If the users themselves could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved...
    Resource Type:
    Research Paper
    Full Text:
    , Lida Li, Weng-Keen Wong, Margaret Burnett, Thomas Dietterich, Erin Sullivan, Jonathan Herlocker

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5 Transductive Optimization of Top k Precision 57 5.1 Introduction

  • Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

    Creator:
    Hooper, Samuel
    Abstract:
    Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and influential environmental conditions. In this research, we considered both spatial and temporal scale and the influence each has on predicting broad-scale distributions of two disparate...
    Resource Type:
    Masters Thesis
    Full Text:
    . References Addicott, John F., John M. Aho, Michael F. Antolin, Dianna K. Padilla, John S. Richardson, and

  • 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
    Full Text:
    ) Updating of µ(k+1). (d) Updating of ν(k+1). The red arrows show the information flow

  • 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
    Full Text:
    where η ≥ `+ κ. Let M = 〈 ~m1, ~m2, ..., ~mn〉 n ∈ N and Q = 〈~q1, ~q2, ..., ~qk〉 k ∈ N represents real

  • Simultaneous segmentation and classification of bird song using CNN

    Creator:
    Narasimhan, Revathy
    Abstract:
    In bioacoustics, automatic animal voice detection and recognition from audio recordings is an emerging topic for animal preservation. Our research focuses on bird bioacoustics, where the goal is to segment bird syllables from the recording and predict the bird species for the syllables. Traditional methods for this task addresses the...
    Resource Type:
    Masters Thesis
    Full Text:
    single label. K-nearest neighbors and SVM are some of the well know SISL classifiers that have been used