Peng, Xiang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 98-115). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.3 / Chapter 1.2 --- Major Contributions --- p.6 / Chapter 1.3 --- Thesis Outline --- p.7 / Chapter 2 --- Background Study --- p.9 / Chapter 2.1 --- Content-based Image Retrieval --- p.9 / Chapter 2.1.1 --- Image Representation --- p.11 / Chapter 2.1.2 --- High Dimensional Indexing --- p.15 / Chapter 2.1.3 --- Image Retrieval Systems Design --- p.16 / Chapter 2.2 --- Relevance Feedback --- p.19 / Chapter 2.2.1 --- Self-Organizing Map in Relevance Feedback --- p.20 / Chapter 2.2.2 --- Decision Tree in Relevance Feedback --- p.22 / Chapter 2.2.3 --- Bayesian Classifier in Relevance Feedback --- p.24 / Chapter 2.2.4 --- Nearest Neighbor Search in Relevance Feedback --- p.25 / Chapter 2.2.5 --- Support Vector Machines in Relevance Feedback --- p.26 / Chapter 2.3 --- Imbalanced Classification --- p.29 / Chapter 2.4 --- Active Learning --- p.31 / Chapter 2.4.1 --- Uncertainly-based Sampling --- p.33 / Chapter 2.4.2 --- Error Reduction --- p.34 / Chapter 2.4.3 --- Batch Selection --- p.35 / Chapter 2.5 --- Convex Optimization --- p.35 / Chapter 2.5.1 --- Overview of Convex Optimization --- p.35 / Chapter 2.5.2 --- Linear Program --- p.37 / Chapter 2.5.3 --- Quadratic Program --- p.37 / Chapter 2.5.4 --- Quadratically Constrained Quadratic Program --- p.37 / Chapter 2.5.5 --- Cone Program --- p.38 / Chapter 2.5.6 --- Semi-definite Program --- p.39 / Chapter 3 --- Imbalanced Learning with BMPM for CBIR --- p.40 / Chapter 3.1 --- Research Motivation --- p.41 / Chapter 3.2 --- Background Review --- p.42 / Chapter 3.2.1 --- Relevance Feedback for CBIR --- p.42 / Chapter 3.2.2 --- Minimax Probability Machine --- p.42 / Chapter 3.2.3 --- Extensions of Minimax Probability Machine --- p.44 / Chapter 3.3 --- Relevance Feedback using BMPM --- p.45 / Chapter 3.3.1 --- Model Definition --- p.45 / Chapter 3.3.2 --- Advantages of BMPM in Relevance Feedback --- p.46 / Chapter 3.3.3 --- Relevance Feedback Framework by BMPM --- p.47 / Chapter 3.4 --- Experimental Results --- p.47 / Chapter 3.4.1 --- Experiment Datasets --- p.48 / Chapter 3.4.2 --- Performance Evaluation --- p.50 / Chapter 3.4.3 --- Discussions --- p.53 / Chapter 3.5 --- Summary --- p.53 / Chapter 4 --- BMPM Active Learning for CBIR --- p.55 / Chapter 4.1 --- Problem Statement and Motivation --- p.55 / Chapter 4.2 --- Background Review --- p.57 / Chapter 4.3 --- Relevance Feedback by BMPM Active Learning . --- p.58 / Chapter 4.3.1 --- Active Learning Concept --- p.58 / Chapter 4.3.2 --- General Approaches for Active Learning . --- p.59 / Chapter 4.3.3 --- Biased Minimax Probability Machine --- p.60 / Chapter 4.3.4 --- Proposed Framework --- p.61 / Chapter 4.4 --- Experimental Results --- p.63 / Chapter 4.4.1 --- Experiment Setup --- p.64 / Chapter 4.4.2 --- Performance Evaluation --- p.66 / Chapter 4.5 --- Summary --- p.68 / Chapter 5 --- Large Scale Learning with BMPM --- p.70 / Chapter 5.1 --- Introduction --- p.71 / Chapter 5.1.1 --- Motivation --- p.71 / Chapter 5.1.2 --- Contribution --- p.72 / Chapter 5.2 --- Background Review --- p.72 / Chapter 5.2.1 --- Second Order Cone Program --- p.72 / Chapter 5.2.2 --- General Methods for Large Scale Problems --- p.73 / Chapter 5.2.3 --- Biased Minimax Probability Machine --- p.75 / Chapter 5.3 --- Efficient BMPM Training --- p.78 / Chapter 5.3.1 --- Proposed Strategy --- p.78 / Chapter 5.3.2 --- Kernelized BMPM and Its Solution --- p.81 / Chapter 5.4 --- Experimental Results --- p.82 / Chapter 5.4.1 --- Experimental Testbeds --- p.83 / Chapter 5.4.2 --- Experimental Settings --- p.85 / Chapter 5.4.3 --- Performance Evaluation --- p.87 / Chapter 5.5 --- Summary --- p.92 / Chapter 6 --- Conclusion and Future Work --- p.93 / Chapter 6.1 --- Conclusion --- p.93 / Chapter 6.2 --- Future Work --- p.94 / Chapter A --- List of Symbols and Notations --- p.96 / Chapter B --- List of Publications --- p.98 / Bibliography --- p.100
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_325956 |
| Date | January 2007 |
| Contributors | Peng, Xiang., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, xii, 115 leaves : ill. ; 30 cm. |
| Rights | Use 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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