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Many learning models have been proposed for various tasks in visual computing. Popular examples include hidden Markov models and support vector machines. Recently, sparse-representation-based learning methods have attracted a lot of attention in the computer vision field, largely because of their impressive performance in many applications.

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    Date Created
    2014
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  • Text
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    Note
    • Partial requirement for: Ph.D., Arizona State University, 2014
      Note type
      thesis
    • Includes bibliographical references (p. 106-114)
      Note type
      bibliography
    • Field of study: Computer science

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    by Qiang Zhang

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