Multiple classifier systems : 5th international workshop, MCS 2004, Cagliari, Italy, June 9-11, 2004 : proceedings
The fusion of di?erent information sourcesis a persistent and intriguing issue. It hasbeenaddressedforcenturiesinvariousdisciplines,includingpoliticalscience, probability and statistics, system reliability assessment, computer science, and distributed detection in communications. Early seminal work...
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| Edition sous un autre format: | • Multiple classifier systems, 5th international workshop, MCS 2004, Cagliari, Italy, June 9-11, 2004, proceedings, Fabio Roli, Josef Kittler, Terry Windeatt (eds.), Berlin, Springer, 2004, 1 vol. (XII-386 p.), Lecture notes in computer science, 3-540-22144-1 • Multiple Classifier Systems, Texte imprimé, 9783662202890 |
Indholdsfortegnelse:
- Invited Papers
- Classifier Ensembles for Changing Environments
- A Generic Sensor Fusion Problem: Classification and Function Estimation
- Bagging and Boosting
- AveBoost2: Boosting for Noisy Data
- Bagging Decision Multi-trees
- Learn++.MT: A New Approach to Incremental Learning
- Beyond Boosting: Recursive ECOC Learning Machines
- Exact Bagging with k-Nearest Neighbour Classifiers
- Combination Methods
- Yet Another Method for Combining Classifiers Outputs: A Maximum Entropy Approach
- Combining One-Class Classifiers to Classify Missing Data
- Combining Kernel Information for Support Vector Classification
- Combining Classifiers Using Dependency-Based Product Approximation with Bayes Error Rate
- Combining Dissimilarity-Based One-Class Classifiers
- A Modular System for the Classification of Time Series Data
- A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
- Classifier Fusion Using Triangular Norms
- Dynamic Integration of Regression Models
- Dynamic Classifier Selection by Adaptive k-Nearest-Neighbourhood Rule
- Design Methods
- Spectral Measure for Multi-class Problems
- The Relationship between Classifier Factorisation and Performance in Stochastic Vector Quantisation
- A Method for Designing Cost-Sensitive ECOC
- Building Graph-Based Classifier Ensembles by Random Node Selection
- A Comparison of Ensemble Creation Techniques
- Multiple Classifiers System for Reducing Influences of Atypical Observations
- Sharing Training Patterns among Multiple Classifiers
- Performance Analysis
- First Experiments on Ensembles of Radial Basis Functions
- Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias Variance Analysis
- Building Diverse Classifier Outputs to Evaluate the Behavior of Combination Methods: The Case of TwoClassifiers
- An Empirical Comparison of Hierarchical vs. Two-Level Approaches to Multiclass Problems
- Experiments on Ensembles with Missing and Noisy Data
- Applications
- Induced Decision Fusion in Automated Sign Language Interpretation: Using ICA to Isolate the Underlying Components of Sign
- Ensembles of Classifiers Derived from Multiple Prototypes and Their Application to Handwriting Recognition
- Network Intrusion Detection by a Multi-stage Classification System
- Application of Breiman s Random Forest to Modeling Structure-Activity Relationships of Pharmaceutical Molecules
- Experimental Study on Multiple LDA Classifier Combination for High Dimensional Data Classification
- Physics-Based Decorrelation of Image Data for Decision Level Fusion in Face Verification
- High Security Fingerprint Verification by Perceptron-Based Fusion of Multiple Matchers
- Second Guessing a Commercial Black Box Classifier by an In House Classifier: Serial Classifier Combination in a Speech Recognition Application.