模式识别及支持向量机 Pattern recognition with support vector machines
点此进入淘宝搜索页搜索分類: 图书,自然科学,数学,运筹学,
作者： Seong-Whan Lee著
出 版 社： 湖南文艺出版社
出版时间： 2002-12-1字数：版次： 1页数： 420印刷时间： 2006/12/01开本：印次：纸张： 胶版纸I S B N ： 9783540440161包装： 平装编辑推荐
The LNCS series reports state-of-the-art results in computer science research,development,and education,at a high level and in both printed and electronic form.Enjoying tight cooperation with the R&D community,with numerous individuals,as well as with prestigious organizations and societies,LNCS has grown into the most comprehensive computer science resarch forum available.
The scope of LNCS,including its subseries LNAI,spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields.The type of material publised traditionally includes.
-proceedings(published in time for the respective conference)
-post-proceedings(consisting of thoroughly revised final full papers)
-research monographs(which may be basde on outstanding PhD work,research projects,technical reports,etc.)
内容简介
This book constitutes the refereed proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002, held in Niagara Falls, Canada in August 2002.The 16 revised full papers and 14 poster papers presented together with two invited contributions were carefully reviewed and selected from 57 full paper submissions. The papers presented span the whole range of topics in pattern recognition with support vector machines from computational theories to implementations and applications.
目录
Invited Papers
Predicting Signal Peptides with Support Vector Machines
Scaling Large Learning Problems with Hard Parallel Mixtures
Computational Issues
On the Generalization of Kernel Machines
Kernel Whitening for One-Class Classification
A Fast SVM Training Algorithm
Support Vector Machines with Embedded Reject Option
Object Recognition
Image Kernels
Combining Color and Shape Information for Appearance-Based Object Recognition Using Ultrametric Spin Glass-Markov Random Fields
Maintenance Training of Electric Power Facilities Using Object Recognition by SVM
Kerneltron: Support Vector 'Machine' in Silicon
Pattern Recognition
Advances in Component-Based Face Detection
Support Vector Learning for Gender Classification Using Audio and Visual Cues: A Comparison
Analysis of Nonstationary Time Series Using Support Vector Machines
Recognition of Consonant-Vowel (CV) Units of Speech in a Broadcast News Corpus Using Support Vector Machines
Applications
Anomaly Detection Enhanced Classification in Computer Intrusion Detection
Sparse Correlation Kernel Analysis and Evolutionary Algorithm-Based Modeling of the Sensory Activity
Applications of Support Vector Machines for Pattern Recognition:A Survey
Typhoon Analysis and Data Mining with Kernel Methods
Poster Papers
Support Vector Features and the Role of Dimensionality in Face Authentication
Face Detection Based on Cost-Sensitive Support Vector Machines
Real-Time Pedestrian Detection Using Support Vector Machines
Forward Decoding Kernel Machines:A Hybrid HMM/SVM Approach to Sequence Recognition
……
Author Index
