Biometric Authentication : A Machine Learning Approach (Hardcover)

S.Y. Kung, M.W. Mak, S.H. Lin

Biometric Authentication : A Machine Learning Approach (Hardcover)
  • 出版商: Prentice Hall
  • 出版日期: 2004-09-24
  • 定價: $4,960
  • 售價: 8.0 折 $3,968
  • 語言: 英文
  • 頁數: 496
  • 裝訂: Hardcover
  • ISBN: 0131478249
  • ISBN-13: 9780131478244
  • 相關分類: Machine Learning

    • 立即出貨(限量) (庫存=3)

買這商品的人也買了...

相關主題

商品描述

Table of Contents:

Preface.

1. Overview.

    Introduction.

    Biometric Authentication Methods.

    Face Recognition: Reality and Challenge.

    Speaker Recognition: Reality and Challenge.

    Road Map of the Book.

2. Biometric Authentication Systems.

    Introduction.

    Design Tradeoffs.

    Feature Extraction.

    Adaptive Classifiers.

    Visual-Based Feature Extraction and Pattern Classification.

    Audio-Based Feature Extraction and Pattern Classification.

    Concluding Remarks.

3. Expectation-Maximization Theory.

    Introduction.

    Traditional Derivation of EM.

    An Entropy Interpretation.

    Doubly-Stochastic EM.

    Concluding Remarks.

4. Support Vector Machines.

    Introduction.

    Fisher's Linear Discriminant Analysis.

    Linear SVMs: Separable Case.

    Linear SVMs: Fuzzy Separation.

    Nonlinear SVMs.

    Biometric Authentication Application Examples.

5. Multi-Layer Neural Networks.

    Introduction.

    Neuron Models.

    Multi-Layer Neural Networks.

    The Back-Propagation Algorithms.

    Two-Stage Training Algorithms.

    Genetic Algorithm for Multi-Layer Networks.

    Biometric Authentication Application Examples.

6. Modular and Hierarchical Networks.

    Introduction.

    Class-Based Modular Networks.

    Mixture-of-Experts Modular Networks.

    Hierarchical Machine Learning Models.

    Biometric Authentication Application Examples.

7. Decision-Based Neural Networks.

    Introduction.

    Basic Decision-Based Neural Networks.

    Hierarchical Design of Decision-Based Learning Models.

    Two-Class Probabilistic DBNNs.

    Multiclass Probabilistic DBNNs.

    Biometric Authentication Application Examples.

8. Biometric Authentication by Face Recognition.

    Introduction.

    Facial Feature Extraction Techniques.

    Facial Pattern Classification Techniques.

    Face Detection and Eye Localization.

    PDBNN Face Recognition System Case Study.

    Application Examples for Face Recognition Systems.

    Concluding Remarks.

9. Biometric Authentication by Voice Recognition.

    Introduction.

    Speaker Recognition.

    Kernel-Based Probabilistic Speaker Models.

    Handset and Channel Distortion.

    Blind Handset-Distortion Compensation.

    Speaker Verification Based on Articulatory Features.

    Concluding Remarks.

10. Multicue Data Fusion.

    Introduction.

    Sensor Fusion for Biometrics.

    Hierarchical Neural Networks for Sensor Fusion.

        Multisample Fusion.

    Audio and Visual Biometric Authentication.

    Concluding Remarks.

Appendix A. Convergence Properties of EM.

Appendix B. Average DET Curves.

Appendix C. Matlab Projects.

    Matlab Project 1: GMMs and RBF Networks for Speech Pattern Recognition.

    Matlab Project 2: SVMs for Pattern Classification.

Bibliography.

Index.

商品描述(中文翻譯)

目錄：

前言
1. 概述
- 簡介
- 生物識別方法
- 人臉識別：現實與挑戰
- 語音識別：現實與挑戰
- 本書路線圖
2. 生物識別系統
- 簡介
- 設計取捨
- 特徵提取
- 適應性分類器
- 基於視覺的特徵提取和模式分類
- 基於音頻的特徵提取和模式分類
- 總結
3. 期望最大化理論
- 簡介
- 傳統EM推導
- 熵解釋
- 雙隨機EM
- 總結
4. 支持向量機
- 簡介
- Fisher線性判別分析
- 線性SVM：可分離情況

類似商品