Multiple Classifier Systems 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007. Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Haindl, Michal (Επιμελητής έκδοσης), Kittler, Josef (Επιμελητής έκδοσης), Roli, Fabio (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
• Σειρά: Lecture Notes in Computer Science, 4472
• Θέματα: Computer science.; Computers.; Artificial intelligence.; Image processing.; Pattern recognition.; Biometrics (Biology).; Computer Science.; Pattern Recognition.; Image Processing and Computer Vision.; Artificial Intelligence (incl. Robotics).; Biometrics.; Computation by Abstract Devices.

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 discussi...

Πίνακας περιεχομένων:

• 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 in One-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 Gene Expression 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.