模式识别机器智能与生物特征识别

作者:王申培 编

页数:866

出版时间:2011-7

价格:138.00元

isbn号码:9787040331394

具体描述

《模式识别、机器智能与生物特征识别(英文版)》介绍广泛应用的人工智能技术——模式识别及其应用的最新进展，收集了世界一流的模式识别、人工智能和生物特征识别技术领域专家编写的31章内容，涵盖模式识别与机器智能、计算机视觉与图像处理、人脸识别与取证、生物特征身份验证等多方面结合的研究。其应用跨越多个领域，从工程、科学研究和实验，到生物医学和医学诊断，再到身份认证和国土安全。此外，《模式识别、机器智能与生物特征识别(英文版)》还介绍了人类行为的计算机建模和仿真。

《模式识别、机器智能与生物特征识别(英文版)》是计算机与信息类以及通信与控制类专业研究生和相关研究人员的必备参考书。

P0trckS.P.Wang（王申培）美国东北大学教授，上海华东师大紫江学者，台湾科技大学客座教授。

作者简介

S.P. Wang（王申培）美国东北大学教授，上海华东师大紫江学者，台湾科技大学客座教授。

目录信息

Part I: Pattern Recognition and Machine Intelligence
1 A Review of Applications of Evolutionary Algorithms in Pattern Recognition
1.1 Introduction
1.2 Basic Notions of Evolutionary Algorithms
1.3 A Review of EAs in Pattern Recognition
1.4 Future Research Directions
1.5 Conclusions
References
2 Pattern Discovery and Recognition in Sequences
2.1 Introduction
2.2 Sequence Patterns and Pattern Discovery-A Brief Review.
2.3 Our Pattern Discovery Framework
2.4 Conclusion
References
3 A Hybrid Method of Tone Assessment for Mandarin
CALL System
3.1 Introduction
3.2 Related Work
3.3 Proposed Approach
3.4 Experimental Procedure and Analysis
3.5 Conclusions
References
4 Fusion with Infrared Images for an Improved Performance and Perception
4.1 Introduction
4.2 The Principle of Infrared Imaging
4.3 Fusion with Infrared Images
4.4 Applications
4.5 Summary
References
5 Feature Selection and Ranking for Pattern
Classification in Wireless Sensor Networks
5.1 Introduction
5.2 General Approach
5.3 Sensor Ranking
5.4 Experiments
5.5 Summary, Discussion and Conclusions
References
6 Principles and Applications of RIDED-2D-A Robust Edge Detection Method in Range Images
6.1 Introduction
6.2 Definitions and Analysis
6.3 Principles of Instantaneous Denoising and Edge Detection
6.4 Experiments and Evaluations
6.5 Discussions and Applications
6.6 Conclusions and Prospects
References
Part Ⅱ: Computer Vision and Image Processing Lens Shading Correction for Dirt Detection
7.1 Introduction
7.2 Background
7.3 Our Proposed Method
7.4 Experimental Results
7.5 Conclusions
References
Using Prototype-Based Classification for Automatic Knowledge Acquisition
8.1 Introduction
8.2 Prototype-Based Classification
8.3 Methodology
8.4 Application
8.5 Results
8.6 Conclusion
References
9 Tracking Deformable Objects with Evolving Templates forReal-Time Machine Vision
9.1 Introduction
9.2 Problem Formulation
9.3 Search Framework for Computing Template Position
9.4 Updating Framework for Computing Template Changes
……
Part Ⅲ：Face Recognition and Forensics
PartⅣ：Biometric Authentication
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