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020 _a9783642023262
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024 7 _a10.1007/978-3-642-02326-2
_2doi
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072 7 _aCOM016000
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072 7 _aUYQP
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082 0 4 _a006.4
_223
245 1 0 _aMultiple Classifier Systems
_h[electronic resource] :
_b8th International Workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009, Proceedings /
_cedited by Jón Atli Benediktsson, Josef Kittler, Fabio Roli.
250 _a1st ed. 2009.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2009.
300 _aXI, 540 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v5519
505 0 _aECOC, Boosting and Bagging -- The Bias Variance Trade-Off in Bootstrapped Error Correcting Output Code Ensembles -- Recoding Error-Correcting Output Codes -- Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting -- Multi-class Boosting with Class Hierarchies -- MCS in Remote Sensing -- Hybrid Hierarchical Classifiers for Hyperspectral Data Analysis -- Multiple Classifier Combination for Hyperspectral Remote Sensing Image Classification -- Ensemble Strategies for Classifying Hyperspectral Remote Sensing Data -- Unbalanced Data and Decision Templates -- Optimal Mean-Precision Classifier -- A Multiple Expert Approach to the Class Imbalance Problem Using Inverse Random under Sampling -- Decision Templates Based RBF Network for Tree-Structured Multiple Classifier Fusion -- Stacked Generalization and Active Learning -- Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors -- Regularized Linear Models in Stacked Generalization -- Active Grading Ensembles for Learning Visual Quality Control from Multiple Humans -- Multiple Classifier Systems for Adversarial Classification Tasks -- Concept Drift, Missing Values and Random Forest -- Incremental Learning of Variable Rate Concept Drift -- Semi-supervised Co-update of Multiple Matchers -- Handling Multimodal Information Fusion with Missing Observations Using the Neutral Point Substitution Method -- Influence of Hyperparameters on Random Forest Accuracy -- SVM Ensembles -- Ensembles of One Class Support Vector Machines -- Disturbing Neighbors Ensembles for Linear SVM -- Fusion of Graphs, Concepts and Categorical Data -- A Labelled Graph Based Multiple Classifier System -- Cluster Ensembles Based on Vector Space Embeddings of Graphs -- Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data -- True Path Rule Hierarchical Ensembles -- Clustering -- A Study of Semi-supervised Generative Ensembles -- Hierarchical Ensemble Support Cluster Machine -- Multi-scale Stacked Sequential Learning -- Unsupervised Hierarchical Weighted Multi-segmenter -- Ant Clustering Using Ensembles of Partitions -- Classifier and Feature Selection -- Selective Ensemble under Regularization Framework -- Criteria Ensembles in Feature Selection -- Network Protocol Verification by a Classifier Selection Ensemble -- Supervised Selective Combining Pattern Recognition Modalities and Its Application to Signature Verification by Fusing On-Line and Off-Line Kernels -- Theory of MCS -- Improved Uniformity Enforcement in Stochastic Discrimination -- An Information Theoretic Perspective on Multiple Classifier Systems -- Constraints in Weighted Averaging -- FaSS: Ensembles for Stable Learners -- MCS Methods and Applications -- Classifying Remote Sensing Data with Support Vector Machines and Imbalanced Training Data -- Terrain Segmentation with On-Line Mixtures of Experts for Autonomous Robot Navigation -- Consistency Measure of Multiple Classifiers for Land Cover Classification by Remote Sensing Image -- Target Identification from High Resolution Remote Sensing Image by Combining Multiple Classifiers -- Neural Network Optimization for Combinations in Identification Systems -- MLP, Gaussian Processes and Negative Correlation Learning for Time Series Prediction -- Diversity-Based Classifier Selection for Adaptive Object Tracking -- Ensemble Based Data Fusion for Gene Function Prediction -- A Cascade Multiple Classifier System for Document Categorization -- Maximum Membership Scale Selection -- An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets -- A Study of Random Linear Oracle Ensembles -- Stacking for Ensembles of Local Experts in Metabonomic Applications -- Boosting Support Vector Machines Successfully -- Invited Papers -- Manifold Learning for Multi-classifier Systems via Ensembles -- When Semi-supervised Learning Meets Ensemble Learning.
520 _aThis book constitutes the refereed proceedings of the 8th International Workshop on Multiple Classifier Systems, MCS 2009, held in Reykjavik, Iceland, in June 2009. The 52 revised full papers presented together with 2 invited papers were carefully reviewed and selected from more than 70 initial submissions. The papers are organized in topical sections on ECOC boosting and bagging, MCS in remote sensing, unbalanced data and decision templates, stacked generalization and active learning, concept drift, missing values and random forest, SVM ensembles, fusion of graphics, concepts and categorical data, clustering, and finally theory, methods and applications of MCS.
650 0 _aPattern recognition systems.
_93953
650 0 _aComputer programming.
_94169
650 0 _aComputer vision.
_9147325
650 0 _aArtificial intelligence.
_93407
650 0 _aBiometric identification.
_911407
650 0 _aComputer science.
_99832
650 1 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aProgramming Techniques.
_9147326
650 2 4 _aComputer Vision.
_9147327
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aBiometrics.
_932763
650 2 4 _aTheory of Computation.
_9147328
700 1 _aBenediktsson, Jón Atli.
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700 1 _aKittler, Josef.
_eeditor.
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_9147330
700 1 _aRoli, Fabio.
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_9147331
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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856 4 0 _uhttps://doi.org/10.1007/978-3-642-02326-2
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