http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Intro -- Contents -- Preface -- About the Authors -- 1. Introduction to Advanced Medical Biometrics -- 1.1 What isMedical Biometrics? -- 1.2 TraditionalMedical Biometrics -- 1.3 AdvancedMedical Biometrics -- 1.3.1 Advanced signal acquisition -- 1.3.2 Advanced feature extraction -- 1.3.3 Advanced classification methods -- 1.4 Outline of this Book -- Part 1: Tongue and Face Image Analysis -- 2. Evolutionary Ensemble Model for Disease Detection Using Tongue Images -- 2.1 Introduction -- 2.2 Tongue Image Acquisition and Feature Extraction -- 2.2.1 Database construction -- 2.2.2 Feature extraction
2.2.2.1 Color Alignment features -- 2.2.2.2 Color Gamut features -- 2.2.2.3 Texture Alignment features -- 2.2.2.4 Texture Gabor features -- 2.2.2.5 Geometry FFT features -- 2.3 Balanced Evolutionary Semi-stacking -- 2.3.1 Problemformulation -- 2.3.2 Balanced evolutionary co-training -- 2.3.2.1 Detailed algorithms of BECT -- 2.3.2.2 Evolutionary operators -- 2.3.3 Balanced evolutionary semi-stacking framework -- 2.3.3.1 Stacking ensemble -- 2.3.3.2 Detailed algorithms of BESS -- 2.4 Experiments -- 2.4.1 Datasets and experimental settings -- 2.4.2 Main results -- 2.4.3 Extensive experiments
2.4.3.1 Ablation experiments on BESS -- 2.4.3.2 Parameter analysis -- 2.4.4 When adding more unlabeled data -- 2.4.5 Experiments on other datasets -- 2.5 Conclusion -- 3. Color Representation and Feature Fusion for Diagnosis Using Sublingual Images -- 3.1 Introduction -- 3.2 RelatedWork -- 3.2.1 Color feature extraction -- 3.2.2 Multiple features learning methods -- 3.3 Dataset Construction -- 3.3.1 Image capture device -- 3.3.2 Data preprocessing -- 3.3.3 Tongue image dataset -- 3.4 Multi-feature LearningMethod -- 3.4.1 Color feature descriptor -- 3.4.1.1 Centroid points
3.4.1.2 Color feature extraction -- 3.4.1.3 Extend the color descriptor into three color spaces -- 3.4.2 Multiple features learning method -- 3.4.2.1 Common and discriminative components -- 3.4.2.2 Reconstruction process -- 3.4.2.3 Common component evaluation -- 3.4.2.4 Discriminative component evaluation -- 3.4.3 Adaptive classifier -- 3.4.4 Objective function -- 3.5 Color Extraction -- 3.5.1 Color detector -- 3.5.2 Effect of proposed color detector -- 3.6 Datasets and Experimental Setting -- 3.6.1 Tongue datasets -- 3.6.2 Public datasets -- 3.6.3 Experimental setting
3.6.4 Experiment results on three datasets -- 3.6.5 Parameters' analysis -- 3.7 Conclusion -- 4. Multi-feature Learning Model for Diagnosis Using Face Skin Images -- 4.1 Introduction -- 4.2 Face Image Capture Device, Dataset, and Feature Extraction -- 4.2.1 Image capture device -- 4.2.2 Face skin images dataset -- 4.2.3 Face skin images preprocessing -- 4.2.4 Feature extraction -- 4.2.4.1 Color feature extraction using centroid points -- 4.2.4.2 Quantitative color features -- 4.2.4.3 Color feature computed using PCA -- 4.2.4.4 Texture feature extraction using GLCM technique -- 4.3 Methods -- 4.3.1 Latent variables projection.
Includes bibliographical references and index.
Advances In pattern analysis and intelligent sensing ; vol. 2
Singapore : World Scientific Publishing Company,c2026