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Filtering by: Creator Lam, Adam Q. Remove constraint Creator: Lam, Adam Q. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • 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:
    AN ABSTRACT OF THE DISSERTATION OF Michael Lam for the

  • 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 AN ABSTRACT OF THE THESIS OF Michael Lam for the degree of Master of Science in Computer

  • Sequential supervised learning and conditional random fields

    Creator:
    Ashenfelter, Adam J.
    Abstract:
    Supervised learning is concerned with discovering the relationship between example sets of features and their corresponding classes. The traditional supervised learning formulation assumes that all examples are independent from one another. The order of the examples contains no information. Nonetheless, many problems have a sequential nature. Classifiers for these problems...
    Resource Type:
    Masters Thesis
    Full Text:
    thesis.dvi c© Copyright by Adam J. Ashenfelter December 4, 2003

  • An Anthology of Next-Generation WSNs and Transformative IoT Use-Cases

    Creator:
    Williams, Jennifer M.
    Abstract:
    The Internet of Things (IoT) paradigm brought an ever-increasing dependence on low-power devices to collect sensor data and transmit that information to the cloud, placing greater demand on connectivity and lifespan. In response, rapid worldwide innovation demonstrates the trade-offs in processing, communication, and energy consumption with diverse approaches to low-power...
    Resource Type:
    Dissertation
    Full Text:
    densely-scalable WSNs for logistics & asset manage- ment (LAM). Next, this research enhances the WSN

  • A Generation Prioritization Method for Power System Restoration with Renewable Resources

    Creator:
    Mate, Adam
    Abstract:
    The electrical grid is a key component of the Nation's critical infrastructure. Its continuous and reliable operation is of vital importance; any system-wide disruption would have a debilitating impact on crucial services, public health and safety, the economy, and the national security of the United States. High-impact low-frequency events pose...
    Resource Type:
    Dissertation
    Full Text:
    Restoration with Renewable Resources AN ABSTRACT OF THE DISSERTATION OF Adam Mate for the degree of Doctor

  • An ultra low voltage micropower GPS receiver RF front-end for wildlife tracking

    Creator:
    Heiberg, Adam C.
    Abstract:
    A fully integrated CMOS GPS receiver RF front end optimized for low power operation is presented. The system operates with a supply voltage down to 250 mV. A prototype has been fabricated in a 0.13μm CMOS process and includes a low voltage LNA, quadrature oscillators, and quadrature mixers. It exhibits...
    Resource Type:
    Masters Thesis
    Full Text:
    1 AN ABSTRACT OF THE THESIS OF Adam C. Heiberg for the degree of

  • Analysis and modeling of single-ended and differential spiral inductors in silicon-based RFICs

    Creator:
    Watson, Adam C.
    Abstract:
    A new comprehensive wide-band compact modeling methodology for single-ended spiral inductors and differential spiral inductors is presented. The new modeling methodology creates an equivalent circuit model consisting of frequency-independent circuit elements for use in circuit simulators. A fast automated extraction procedure is developed for determining the circuit element values from...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Adam C. Watson for the degree of

  • Instruction fetching, scheduling, and forwarding in a dynamic multithreaded processor

    Creator:
    Browning, Adam W.
    Abstract:
    Dynamic multithreaded processors attempt to increase the performance of a single sequential program by dynamically extracting threads from sources such as loop iterations. The scheduling of instructions in such a processor plays a vital role in the amount of thread level parallelism that can be extracted and thus the overall...
    Resource Type:
    Masters Thesis
    Full Text:
    Multithreaded Processor AN ABSTRACT OF THE THESIS OF Adam W. Browning for the degree of Master of Science

  • Deep ultraviolet solid-state laser development

    Creator:
    Dutton, David A. (David Adam)
    Abstract:
    There is a new possibility of generating deep ultraviolet laser radiation from a solid-state source. With recent advances in material development, a new nonlinear optical crystal provides a greater damage threshold than current materials making higher conversion efficiencies possible. This thesis examines the possibility of using this crystal to generate...
    Resource Type:
    Masters Thesis
    Full Text:
    angle of 11 degrees less than the model prediction. Possible electro-optic Q-switching is examined

  • Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms

    Creator:
    Ibrahim, Shahana
    Abstract:
    Crowdsourcing is a popular paradigm to address the high demands for labeled data in big data deluge. It aims to produce accurate labels by effectively integrating noisy, non-expert labeling from crowdsourced workers (annotators). The machine learning community has been studying effective crowdsourcing methods for many years, and many models and...
    Resource Type:
    Masters Thesis
    Full Text:
    following procedure to identify Am from Zm. First, let us normalize the columns of Zm via, Zm(:, q) = Zm