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Filtering by: Subject Signal processing -- Mathematical models Remove constraint Subject: Signal processing -- Mathematical models Decade 2010-2019 Remove constraint Decade: 2010-2019

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  • Applied color processing

    Creator:
    Zhang, Heng
    Abstract:
    The quality of a digital image pipeline relies greatly on its color reproduction which should at a minimum handle the color constancy, and the final judgment of the excellence of the pipeline is made through subjective observations by humans. This dissertation addresses a few topics surrounding the color processing of...
    Resource Type:
    Dissertation
    Full Text:
    Engineering presented on November 29, 2011. Title: Applied Color Processing. Abstract approved

  • 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:
    classification model for the learning problem. The thesis also analyzes the learnability of the superset label

  • GPU-Based Fluid-Structure Interaction using Immersed Boundary Methods

    Creator:
    Minar, Christopher
    Abstract:
    Engineering applications often require fast, accurate solutions of fluid flow around freely moving bodies. The massive parallelism enabled by graphics processing unit (GPU) architecture enables high performance, offering a promising alternative to traditional solver acceleration via multicore central processing units (CPU). However, fully harnessing GPU parallelism requires specialized algorithms and...
    Resource Type:
    Masters Thesis
    Full Text:
    . The massive parallelism enabled by graphics processing unit (GPU) architecture enables high

  • 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:
    Washington with a model that simultaneously reflects local-scale heterogeneity and broad-scale homogeneity