Multiple classifier systems : Third International Workshop, MCS 2002 Cagliari, Italy, June 24 26, 2002 : proceedings
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| Muut tekijät: | , |
| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Sarja: | Lecture notes in computer science
2364 |
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| Linkit: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Multiple classifier systems, Third International Workshop, MCS 2002, Cagliari, Italy, June 24-26, 2002, Proceedings, Fabio Roli, Josef Kittler (eds.), Berlin, Springer, 2002, 1 vol. (XI-335 p.), Lecture notes in computer science, 3-540-43818-1 • Multiple Classifier Systems, Texte imprimé, 9783662165973 |
Sisällysluettelo:
- Invited Papers
- Multiclassifier Systems: Back to the Future
- Support Vector Machines, Kernel Logistic Regression and Boosting
- Multiple Classification Systems in the Context of Feature Extraction and Selection
- Bagging and Boosting
- Boosted Tree Ensembles for Solving Multiclass Problems
- Distributed Pasting of Small Votes
- Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy
- Highlighting Hard Patterns via AdaBoost Weights Evolution
- Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse
- Ensemble Learning and Neural Networks
- Multistage Neural Network Ensembles
- Forward and Backward Selection in Regression Hybrid Network
- Types of Multinet System
- Discriminant Analysis and Factorial Multiple Splits in Recursive Partitioning for Data Mining
- Design Methodologies
- New Measure of Classifier Dependency in Multiple Classifier Systems
- A Discussion on the Classifier Projection Space for Classifier Combining
- On the General Application of the Tomographic Classifier Fusion Methodology
- Post-processing of Classifier Outputs in Multiple Classifier Systems
- Combination Strategies
- Trainable Multiple Classifier Schemes for Handwritten Character Recognition
- Generating Classifier Ensembles from Multiple Prototypes and Its Application to Handwriting Recognition
- Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data
- Stacking with Multi-response Model Trees
- On Combining One-Class Classifiers for Image Database Retrieval
- Analysis and Performance Evaluation
- Bias Variance Analysis and Ensembles of SVM
- An Experimental Comparison of Fixed and Trained Fusion Rules for Crisp Classifier Outputs
- Reduction of the Boasting Bias of Linear Experts.-Analysis of Linear and Order Statistics Combiners for Fusion of Imbalanced Classifiers
- Applications
- Boosting and Classification of Electronic Nose Data
- Content-Based Classification of Digital Photos
- Classifier Combination for In Vivo Magnetic Resonance Spectra of Brain Tumours
- Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach
- A Multi-expert System for Movie Segmentation
- Decision Level Fusion of Intramodal Personal Identity Verification Experts
- An Experimental Comparison of Classifier Fusion Rules for Multimodal Personal Identity Verification Systems.