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  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
    Resource Type:
    Dissertation
    Full Text:
    , representing Computer Science Director of the School of Electrical Engineering and Computer Science Dean of

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    Computer Science Director of the School of Electrical Engineering and Computer Science Dean of the

  • Listing as a Potential Connection between Sets of Outcomes and Counting Processes

    Creator:
    Erickson, Sarah A.
    Abstract:
    Counting problems are rich in opportunities for students to make meaningful mathematical connections and develop non-algorithmic thinking; their accessible nature and applications to computer science make counting problems a valuable part of mathematics curricula. However, students struggle in various ways with counting, and while previous studies have indicated that listing...
    Resource Type:
    Masters Thesis
    Full Text:
    important than ever due to its applications in computer science, electrical engineering, probability, and

  • Interactive player tracking for videos in American football

    Creator:
    Bawaskar, Amit
    Abstract:
    This thesis presents an interactive software tool for tracking a moving object in a video. In particular, we focus on the problem of tracking a player in American football videos. Object tracking is one of the fundamental problems in computer vision. It is one of the most important components in...
    Resource Type:
    Masters Thesis
    Full Text:
    of Electrical Engineering and Computer Science Dean of the Graduate School I understand that my

  • The density signature

    Creator:
    Migler-VonDollen, Theresa
    Abstract:
    In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
    Resource Type:
    Dissertation
    Full Text:
    : Major Professor, representing Computer Science Director of the School of Electrical Engineering and

  • Network Coding, Random Matrices, and Their Applications to Communication Systems

    Creator:
    Nguyen-Huu, Duong
    Abstract:
    In this work, we study network coding technique, its relation to random matrices, and their applications to communication systems. The dissertation consists of three main contributions. First, we propose efficient algorithms for data synchronization via a broadcast channel using random network coding. Second, we study the resiliency of network coding...
    Resource Type:
    Dissertation
    Full Text:
    of the School of Electrical Engineering and Computer Science Dean of the Graduate School I

  • Protocol design and optimization for wireless networks

    Creator:
    Lertsutthiwong, Monchai
    Abstract:
    We investigate a number of techniques for increasing throughput and quality of media applications over wireless networks. A typical media communication application such as video streaming imposes strict requirements on the delay and throughout of its packets, which unfortunately, cannot be guaranteed by the underlying wireless network due inherently to...
    Resource Type:
    Dissertation
    Full Text:
    Engineering Director of the School of Electrical Engineering and Computer Science Dean of the Graduate

  • Toward Automated Decision-Making in Power Systems Wide-Area Protection

    Creator:
    Meier, Richard John
    Abstract:
    In recent years there have been many improvements in the reliability of critical infrastructure systems. Despite these improvements and despite targeted efforts to improve the operation and control of the electric grid, the power systems industry has seen relatively small advances in this regard. For instance, today's power system is...
    Resource Type:
    Masters Thesis
    Full Text:
    Director of the School of Electrical Engineering and Computer Science Dean of the Graduate School I

  • Hierarchical graphical models for activity recognition in videos

    Creator:
    Amer, Mohamed R.
    Abstract:
    This dissertation addresses the problem of recognizing human activities in videos. Our focus is on activities with stochastic structure, where the activities are characterized by variable space-time arrangements of actions, and conducted by a variable number of actors. These activities occur frequently in sports and surveillance videos. They may appear...
    Resource Type:
    Dissertation
    Full Text:
    Engineering Director of the School of Electrical Engineering and Computer Science Dean of the Graduate

  • Network coding for multi-user wireless networks

    Creator:
    Nguyen, Dong Van
    Abstract:
    Until a few years ago, wireless-capable laptops were considered novelties by many. It is now hard to find a laptop or a hand-held computing device that is not wireless-ready. As wireless devices are becoming commodities, they have also become an indispensable part of the modern society. Not surprisingly, research in...
    Resource Type:
    Dissertation
    Full Text:
    of Doctor of Philosophy in Electrical Engineering and Computer Science presented on June 10, 2009