Lecture Notes in Computer Science : 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings - Terry Windeatt

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Lecture Notes in Computer Science

4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings

By: Terry Windeatt (Editor), Fabio Roli (Editor)

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Paperback | 27 May 2003

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The refereed proceedings of the 4th International Workshop on Multiple Classifier Systems, MCS 2003, held in Guildford, UK in June 2003.

The 40 revised full papers presented with one invited paper were carefully reviewed and selected for presentation. The papers are organized in topical sections on boosting, combination rules, multi-class methods, fusion schemes and architectures, neural network ensembles, ensemble strategies, and applications

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Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Psychology Cognition & Cognitive Psychology Artificial Intelligence Neural Networks & Fuzzy Systems Computer Vision Industry & Industrial Studies Media, Entertainment, Information & Communication Industries Information Technology Industries

Graphical & Digital Media Applications

Data Dependence in Combining Classifiers	p. 1
Boosting with Averaged Weight Vectors	p. 15
Error Bounds for Aggressive and Conservative AdaBoost	p. 25
An Empirical Comparison of Three Boosting Algorithms on Real Data Sets with Artificial Class Noise	p. 35
The Beneficial Effects of Using Multi-net Systems That Focus on Hard Patterns	p. 45
The Behavior Knowledge Space Fusion Method: Analysis of Generalization Error and Strategies for Performance Improvement	p. 55
Reducing the Overconfidence of Base Classifiers when Combining Their Decisions	p. 65
Linear Combiners for Classifier Fusion: Some Theoretical and Experimental Results	p. 74
Comparison of Classifier Selection Methods for Improving Committee Performance	p. 84
Towards Automated Classifier Combination for Pattern Recognition	p. 94
Serial Multiple Classifier Systems Exploiting a Coarse to Fine Output Coding	p. 106
Polychotomous Classification with Pairwise Classifiers: A New Voting Principle	p. 115
Multi-category Classification by Soft-Max Combination of Binary Classifiers	p. 125
A Sequential Scheduling Approach to Combining Multiple Object Classifiers Using Cross-Entropy	p. 135
Binary Classifier Fusion Based on the Basic Decomposition Methods	p. 146
Good Error Correcting Output Codes for Adaptive Multiclass Learning	p. 156
Finding Natural Clusters Using Multi-clusterer Combiner Based on Shared Nearest Neighbors	p. 166
An Ensemble Approach for Data Fusion with Learn++	p. 176
The Practical Performance Characteristics of Tomographically Filtered Multiple Classifier Fusion	p. 186
Accumulated-Recognition-Rate Normalization for Combining Multiple On/Off-Line Japanese Character Classifiers Tested on a Large Database	p. 196
Beam Search Extraction and Forgetting Strategies on Shared Ensembles	p. 206
A Markov Chain Approach to Multiple Classifier Fusion	p. 217
A Study of Ensemble of Hybrid Networks with Strong Regularization	p. 227
Combining Multiple Modes of Information Using Unsupervised Neural Classifiers	p. 236
Neural Net Ensembles for Lithology Recognition	p. 246
Improving Performance of a Multiple Classifier System Using Self-generating Neural Networks	p. 256
Negative Correlation Learning and the Ambiguity Family of Ensemble Methods	p. 266
Spectral Coefficients and Classifier Correlation	p. 276
Ensemble Construction via Designed Output Distortion	p. 286
Simulating Classifier Outputs for Evaluating Parallel Combination Methods	p. 296
A New Ensemble Diversity Measure Applied to Thinning Ensembles	p. 306
Ensemble Methods for Noise Elimination in Classification Problems	p. 317
New Boosting Algorithms for Classification Problems with Large Number of Classes Applied to a Handwritten Word Recognition Task	p. 326
Automatic Target Recognition Using Multiple Description Coding Models for Multiple Classifier Systems	p. 336
A Modular Multiple Classifier System for the Detection of Intrusions in Computer Networks	p. 346
Input Space Transformations for Multi-classifier Systems Based on n-tuple Classifiers with Application to Handwriting Recognition	p. 356
Building Classifier Ensembles for Automatic Sports Classification	p. 366
Classification of Aircraft Maneuvers for Fault Detection	p. 375
Solving Problems Two at a Time: Classification of Web Pages Using a Generic Pair-Wise Multiple Classifier System	p. 385
Design and Evaluation of an Adaptive Combination Framework for OCR Result Strings	p. 395
Author Index	p. 405
Table of Contents provided by Blackwell. All Rights Reserved.

Lecture Notes in Computer Science

4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings

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