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Multiple Classifier Systems: 9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010. Proceedings

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Personen und Körperschaften: Gayar, Neamat (VerfasserIn), Kittler, Josef (Sonstige), Roli, Fabio (Sonstige)
Titel: Multiple Classifier Systems: 9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010. Proceedings/ edited by Neamat Gayar, Josef Kittler, Fabio Roli
Format: E-Book
Sprache: Englisch
veröffentlicht:
Berlin, Heidelberg Springer Berlin Heidelberg 2010
Gesamtaufnahme: SpringerLink
Lecture notes in computer science ; 5997
Schlagwörter:
Buchausg. u.d.T.: Multiple classifier systems, Berlin : Springer, 2010, X, 328 S.
Quelle: Verbunddaten SWB
Zugangsinformationen: Elektronischer Volltext - Campuslizenz
Details
Zusammenfassung: Classifier Ensembles(I) -- Weighted Bagging for Graph Based One-Class Classifiers -- Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers -- New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization -- Incremental Learning of New Classes in Unbalanced Datasets: Learn?+?+?.UDNC -- Tomographic Considerations in Ensemble Bias/Variance Decomposition -- Choosing Parameters for Random Subspace Ensembles for fMRI Classification -- Classifier Ensembles(II) -- An Experimental Study on Ensembles of Functional Trees -- Multiple Classifier Systems under Attack -- SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning -- Unsupervised Change-Detection in Retinal Images by a Multiple-Classifier Approach -- A Double Pruning Algorithm for Classification Ensembles -- Estimation of the Number of Clusters Using Multiple Clustering Validity Indices -- Classifier Diversity -- “Good” and “Bad” Diversity in Majority Vote Ensembles -- Multi-information Ensemble Diversity -- Classifier Selection -- Dynamic Selection of Ensembles of Classifiers Using Contextual Information -- Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems -- Combining Multiple Kernels -- A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities -- Combining Multiple Kernels by Augmenting the Kernel Matrix -- Boosting and Bootstrapping -- Class-Separability Weighting and Bootstrapping in Error Correcting Output Code Ensembles -- Boosted Geometry-Based Ensembles -- Online Non-stationary Boosting -- Handwriting Recognition -- Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting -- Combining Committee-Based Semi-supervised and Active Learning and Its Application to Handwritten Digits Recognition -- Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition -- Applications -- Forecast Combination Strategies for Handling Structural Breaks for Time Series Forecasting -- A Multiple Classifier System for Classification of LIDAR Remote Sensing Data Using Multi-class SVM -- A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation -- A Multi-objective Sequential Ensemble for Cluster Structure Analysis and Visualization and Application to Gene Expression -- Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells -- An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction -- Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network -- Invited Papers -- Some Thoughts at the Interface of Ensemble Methods and Feature Selection -- Multiple Classifier Systems for the Recogonition of Human Emotions -- Erratum -- Erratum.
Umfang: Online-Ressource (X, 328p. 77 illus, digital)
ISBN: 9783642121272
DOI: 10.1007/978-3-642-12127-2