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Study of locally adaptive classification.

Dai, Juan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 36-39). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Previous Work --- p.3 / Chapter 1.2 --- Proposed Framework --- p.5 / Chapter 1.3 --- Overview --- p.6 / Chapter 2 --- Placement of the Local Classifiers --- p.8 / Chapter 2.1 --- The Uncertainty Map --- p.9 / Chapter 2.2 --- Responsibility Mixture Model --- p.11 / Chapter 2.3 --- EM for Parameter Estimation --- p.12 / Chapter 2.3.1 --- E-Step --- p.14 / Chapter 2.3.2 --- M-Step --- p.15 / Chapter 2.3.3 --- Relationship with Gaussian Mixture Mod- els(GMM) --- p.16 / Chapter 3 --- Fusing of Locally Adaptive Classifiers --- p.18 / Chapter 3.1 --- Training --- p.18 / Chapter 3.2 --- Testing --- p.21 / Chapter 4 --- Algorithmic Characteristics --- p.23 / Chapter 4.1 --- Uncertainty Piloted Placement of Local Classifiers --- p.23 / Chapter 4.2 --- Uncertainty Piloted Fusing of Local Classifiers --- p.24 / Chapter 4.3 --- Related Work --- p.25 / Chapter 5 --- Experiments --- p.27 / Chapter 5.1 --- Dimensionality Reduction --- p.27 / Chapter 5.2 --- Two-Class Classification Problem: Gender Classification --- p.29 / Chapter 5.3 --- Multi-Class Classification: Face Recognition --- p.30 / Chapter 5.3.1 --- Varying the Lighting --- p.31 / Chapter 5.3.2 --- Varying the Pose --- p.32 / Chapter 5.3.3 --- Number of Features Extracted --- p.33 / Chapter 6 --- Conclusion --- p.34 / Bibliography --- p.36

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326012
Date January 2007
ContributorsDai, Juan., Chinese University of Hong Kong Graduate School. Division of Information Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, x, 39 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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