Multiple Classifier Systems (Record no. 184621)

MARC details
000 -LEADER
fixed length control field 07556nam a22006255i 4500
001 - CONTROL NUMBER
control field 978-3-540-72523-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423130048.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 100301s2007 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540725237
-- 978-3-540-72523-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-540-72523-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q337.5
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TK7882.P3
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQP
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM016000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQP
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.4
Edition number 23
245 10 - TITLE STATEMENT
Title Multiple Classifier Systems
Medium [electronic resource] :
Remainder of title 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings /
Statement of responsibility, etc edited by Michal Haindl, Josef Kittler, Fabio Roli.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2007.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2007.
300 ## - PHYSICAL DESCRIPTION
Extent XI, 524 p.
Other physical details online resource.
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-- online resource
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490 1# - SERIES STATEMENT
Series statement Image Processing, Computer Vision, Pattern Recognition, and Graphics,
International Standard Serial Number 3004-9954 ;
Volume number/sequential designation 4472
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Kernel-Based Fusion -- Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion -- The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition -- Kernel Combination Versus Classifier Combination -- Deriving the Kernel from Training Data -- Applications -- On the Application of SVM-Ensembles Based on Adapted Random Subspace Sampling for Automatic Classification of NMR Data -- A New HMM-Based Ensemble Generation Method for Numeral Recognition -- Classifiers Fusion in Recognition of Wheat Varieties -- Multiple Classifier Methods for Offline Handwritten Text Line Recognition -- Applying Data Fusion Methods to Passage Retrieval in QAS -- A Co-training Approach for Time Series Prediction with Missing Data -- An Improved Random Subspace Method and Its Application to EEG Signal Classification -- Ensemble Learning Methods for Classifying EEG Signals -- Confidence Based Gating of Colour Features for Face Authentication -- View-Based Eigenspaces with Mixture of Experts for View-Independent Face Recognition -- Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification -- Serial Fusion of Fingerprint and Face Matchers -- Boosting -- Boosting Lite – Handling Larger Datasets and Slower Base Classifiers -- Information Theoretic Combination of Classifiers with Application to AdaBoost -- Interactive Boosting for Image Classification -- Cluster and Graph Ensembles -- Group-Induced Vector Spaces -- Selecting Diversifying Heuristics for Cluster Ensembles -- Unsupervised Texture Segmentation Using Multiple Segmenters Strategy -- Classifier Ensembles for Vector Space Embedding of Graphs -- Cascading for Nominal Data -- Feature Subspace Ensembles -- A Combination of Sample Subsets and Feature Subsets inOne-Against-Other Classifiers -- Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features -- Feature Subspace Ensembles: A Parallel Classifier Combination Scheme Using Feature Selection -- Stopping Criteria for Ensemble-Based Feature Selection -- Multiple Classifier System Theory -- On Rejecting Unreliably Classified Patterns -- Bayesian Analysis of Linear Combiners -- Applying Pairwise Fusion Matrix on Fusion Functions for Classifier Combination -- Modelling Multiple-Classifier Relationships Using Bayesian Belief Networks -- Classifier Combining Rules Under Independence Assumptions -- Embedding Reject Option in ECOC Through LDPC Codes -- Intramodal and Multimodal Fusion of Biometric Experts -- On Combination of Face Authentication Experts by a Mixture of Quality Dependent Fusion Classifiers -- Index Driven Combination of Multiple Biometric Experts for AUC Maximisation -- Q???stack: Uni- and Multimodal Classifier Stacking with Quality Measures -- Reliability-Based Voting Schemes Using Modality-Independent Features in Multi-classifier Biometric Authentication -- Optimal Classifier Combination Rules for Verification and Identification Systems -- Majority Voting -- Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets -- On the Diversity-Performance Relationship for Majority Voting in Classifier Ensembles -- Hierarchical Behavior Knowledge Space -- Ensemble Learning -- A New Dynamic Ensemble Selection Method for Numeral Recognition -- Ensemble Learning in Linearly Combined Classifiers Via Negative Correlation -- Naïve Bayes Ensembles with a Random Oracle -- An Experimental Study on Rotation Forest Ensembles -- Cooperative Coevolutionary Ensemble Learning -- Robust Inference in Bayesian Networks with Application to GeneExpression Temporal Data -- An Ensemble Approach for Incremental Learning in Nonstationary Environments -- Invited Papers -- Multiple Classifier Systems in Remote Sensing: From Basics to Recent Developments -- Biometric Person Authentication Is a Multiple Classifier Problem.
520 ## - SUMMARY, ETC.
Summary, etc These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. Being the seventh in a well-established series of meetings providing an international forum for the discussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic. From more than 80 submissions, the Programme Committee selected 49 - pers to create an interesting scienti?c programme. The special focus of MCS 2007 was on the application of multiple classi?er systems in biometrics. This part- ular application area exercises all aspects of multiple classi?er fusion, from - tramodal classi?er combination, through con?dence-based fusion, to multimodal biometric systems. The sponsorship of MCS 2007 by the European Union N- work of Excellence in Biometrics BioSecure and in Multimedia Understanding through Semantics, Computation and Learning MUSCLE and their assistance in selecting the contributions to the MCS 2007 programme consistent with this theme is gratefully acknowledged.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern recognition systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer vision.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Biometric identification.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Automated Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Vision.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Biometrics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Theory of Computation.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Haindl, Michal.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kittler, Josef.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Roli, Fabio.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540724810
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540838227
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Image Processing, Computer Vision, Pattern Recognition, and Graphics,
-- 3004-9954 ;
Volume number/sequential designation 4472
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-540-72523-7">https://doi.org/10.1007/978-3-540-72523-7</a>
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Koha item type eBooks-CSE-Springer

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