Content-based image retrieval-- a small sample learning approach.

Tao Dacheng. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 70-75). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Content-based Image Retrieval --- p.1 / Chapter 1.2 --- SVM based RF in CBIR --- p.3 / Chapter 1.3 --- DA based RF in CBIR --- p.4 / Chapter 1.4 --- Existing CBIR Engines --- p.5 / Chapter 1.5 --- Practical Applications of CBIR --- p.10 / Chapter 1.6 --- Organization of this thesis --- p.11 / Chapter Chapter 2 --- Statistical Learning Theory and Support Vector Machine --- p.12 / Chapter 2.1 --- The Recognition Problem --- p.12 / Chapter 2.2 --- Regularization --- p.14 / Chapter 2.3 --- The VC Dimension --- p.14 / Chapter 2.4 --- Structure Risk Minimization --- p.15 / Chapter 2.5 --- Support Vector Machine --- p.15 / Chapter 2.6 --- Kernel Space --- p.17 / Chapter Chapter 3 --- Discriminant Analysis --- p.18 / Chapter 3.1 --- PCA --- p.18 / Chapter 3.2 --- KPCA --- p.18 / Chapter 3.3 --- LDA --- p.20 / Chapter 3.4 --- BDA --- p.20 / Chapter 3.5 --- KBDA --- p.21 / Chapter Chapter 4 --- Random Sampling Based SVM --- p.24 / Chapter 4.1 --- Asymmetric Bagging SVM --- p.25 / Chapter 4.2 --- Random Subspace Method SVM --- p.26 / Chapter 4.3 --- Asymmetric Bagging RSM SVM --- p.26 / Chapter 4.4 --- Aggregation Model --- p.30 / Chapter 4.5 --- Dissimilarity Measure --- p.31 / Chapter 4.6 --- Computational Complexity Analysis --- p.31 / Chapter 4.7 --- QueryGo Image Retrieval System --- p.32 / Chapter 4.8 --- Toy Experiments --- p.35 / Chapter 4.9 --- Statistical Experimental Results --- p.36 / Chapter Chapter 5 --- SSS Problems in KBDA RF --- p.42 / Chapter 5.1 --- DKBDA --- p.43 / Chapter 5.1.1 --- DLDA --- p.43 / Chapter 5.1.2 --- DKBDA --- p.43 / Chapter 5.2 --- NKBDA --- p.48 / Chapter 5.2.1 --- NLDA --- p.48 / Chapter 5.2.2 --- NKBDA --- p.48 / Chapter 5.3 --- FKBDA --- p.49 / Chapter 5.3.1 --- FLDA --- p.49 / Chapter 5.3.2 --- FKBDA --- p.49 / Chapter 5.4 --- Experimental Results --- p.50 / Chapter Chapter 6 --- NDA based RF for CBIR --- p.52 / Chapter 6.1 --- NDA --- p.52 / Chapter 6.2 --- SSS Problem in NDA --- p.53 / Chapter 6.2.1 --- Regularization method --- p.53 / Chapter 6.2.2 --- Null-space method --- p.54 / Chapter 6.2.3 --- Full-space method --- p.54 / Chapter 6.3 --- Experimental results --- p.55 / Chapter 6.3.1 --- K nearest neighbor evaluation for NDA --- p.55 / Chapter 6.3.2 --- SSS problem --- p.56 / Chapter 6.3.3 --- Evaluation experiments --- p.57 / Chapter Chapter 7 --- Medical Image Classification --- p.59 / Chapter 7.1 --- Introduction --- p.59 / Chapter 7.2 --- Region-based Co-occurrence Matrix Texture Feature --- p.60 / Chapter 7.3 --- Multi-level Feature Selection --- p.62 / Chapter 7.4 --- Experimental Results --- p.63 / Chapter 7.4.1 --- Data Set --- p.64 / Chapter 7.4.2 --- Classification Using Traditional Features --- p.65 / Chapter 7.4.3 --- Classification Using the New Features --- p.66 / Chapter Chapter 8 --- Conclusion --- p.68 / Bibliography --- p.70

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324728
Date January 2004
ContributorsTao, Dacheng., 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, vii, 75 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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