Abstract Details
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Activity Number:
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251
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract #313381
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Title:
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Functional Data Analysis in Computer Vision
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Author(s):
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Italo Raony Costa Lima*+ and Nedret Billor
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Companies:
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Auburn University and Auburn University
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Keywords:
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Functional Data Analysis ;
Computer Vision ;
Classification ;
Depth function
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Abstract:
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Functional data analysis (FDA) is a subject of increasing activity in the statistical community. The power obtained from considering the information of whole functions, rather than discrete observations has proved to be fruitful.
In what follows we investigate the use of FDA in computer vision problems. Depth-based classification in the framework of functional data is used for the MNIST database of handwritten digits, and the results compared with benchmark algorithms.
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Authors who are presenting talks have a * after their name.
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