Description
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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Contributors
- Zhang, Qiang (Author)
- Li, Baoxin (Thesis advisor)
- Turaga, Pavan (Committee member)
- Wang, Yalin (Committee member)
- Ye, Jieping (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2014
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Note
- Partial requirement for: Ph.D., Arizona State University, 2014Note typethesis
- Includes bibliographical references (p. 106-114)Note typebibliography
- Field of study: Computer science
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Statement of Responsibility
by Qiang Zhang