Abstract/Details

Classification by active testing with applications to imaging and change detection


1999 1999

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Abstract (summary)

In this dissertation, we investigate adaptive strategies for sequential testing, especially those driven by maximizing information gain when the conditional distribution of tests given hypotheses is Gaussian. We implement a classification algorithm in which tests are selected recursively and adaptively on-line. We show that such information-based strategies are statistically sensible and computationally efficient, and accommodate testing at multiple resolutions. Finally, applications are made to change point detection and medical image classification.

Indexing (details)


Subject
Statistics
Classification
0463: Statistics
Identifier / keyword
Pure sciences, Active testing, Change detection, Classification, Imaging, Sequential testing
Title
Classification by active testing with applications to imaging and change detection
Author
Li, Chunming
Number of pages
124
Publication year
1999
Degree date
1999
School code
0118
Source
DAI-B 60/02, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9780599199514, 0599199512
Advisor
Geman, Donald
University/institution
University of Massachusetts Amherst
University location
United States -- Massachusetts
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
9920621
ProQuest document ID
304515090
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/304515090
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