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Efficient dimensionality reduction and one-class classification for content-based image retrieval

thesis
posted on 2009-01-01, 00:00 authored by Yiqing Tu
The thesis investigates various machine learning approaches to reducing data dimensionality, and studies the impact of asymmetric data on learning in image retrieval. Efficient algorithms are proposed to reduce the data dimensionality. Integration strategies for one-class classification are designed to address asymmetric data issue and improve retrieval effectiveness.

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Pagination

ix, 181 p. ; 30 cm.

Material type

thesis

Resource type

thesis

Language

eng

Notes

Degree conferred 2010.

Degree name

Ph.D.

Faculty

Faculty of Science

School

Engineering and Built Environment

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