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Multiple Classifier Systems

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

  • Conference proceedings
  • © 2003

Overview

Editors:
  1. Terry Windeatt

    1. Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, Surrey, UK

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  2. Fabio Roli

    1. Dept. of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2709)

Included in the following conference series:

Conference proceedings info: MCS 2003.

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Table of contents (40 papers)

  1. Fusion Schemes Architectures

    1. Accumulated-Recognition-Rate Normalization for Combining Multiple On/Off-Line Japanese Character Classifiers Tested on a Large Database

      • Ondrej Velek, Stefan Jaeger, Masaki Nakagawa
      Pages 196-205

    2. Beam Search Extraction and Forgetting Strategies on Shared Ensembles

      • V. Estruch, C. Ferri, J. Hernández-Orallo, M. J. Ramírez-Quintana
      Pages 206-216

    3. A Markov Chain Approach to Multiple Classifier Fusion

      • S. P. Luttrell
      Pages 217-226

  2. Neural Network Ensembles

    1. A Study of Ensemble of Hybrid Networks with Strong Regularization

      • Shimon Cohen, Nathan Intrator
      Pages 227-235

    2. Combining Multiple Modes of Information Using Unsupervised Neural Classifiers

      • Khurshid Ahmad, Matthew Casey, Bogdan Vrusias, Panagiotis Saragiotis
      Pages 236-245

    3. Neural Net Ensembles for Lithology Recognition

      • R. O. V. Santos, M. M. B. R. Vellasco, F. A. V. Artola, S. A. B. da Fontoura
      Pages 246-255

    4. Improving Performance of a Multiple Classifier System Using Self-generating Neural Networks

      • Hirotaka Inoue, Hiroyuki Narihisa
      Pages 256-265

  3. Ensemble Strategies

    1. Negative Correlation Learning and the Ambiguity Family of Ensemble Methods

      • Gavin Brown, Jeremy Wyatt
      Pages 266-275

    2. Spectral Coefficients and Classifier Correlation

      • Terry Windeatt, R. Ghaderi, G. Ardeshir
      Pages 276-285

    3. Ensemble Construction via Designed Output Distortion

      • Stefan W. Christensen
      Pages 286-295

    4. Simulating Classifier Outputs for Evaluating Parallel Combination Methods

      • H. Zouari, L. Heutte, Y. Lecourtier, A. Alimi
      Pages 296-305

    5. A New Ensemble Diversity Measure Applied to Thinning Ensembles

      • Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer
      Pages 306-316

    6. Ensemble Methods for Noise Elimination in Classification Problems

      • Sofie Verbaeten, Anneleen Van Assche
      Pages 317-325

  4. Applications

    1. New Boosting Algorithms for Classification Problems with Large Number of Classes Applied to a Handwritten Word Recognition Task

      • Simon Günter, Horst Bunke
      Pages 326-335

    2. Automatic Target Recognition Using Multiple Description Coding Models for Multiple Classifier Systems

      • Widhyakorn Asdornwised, Somchai Jitapunkul
      Pages 336-345

    3. A Modular Multiple Classifier System for the Detection of Intrusions in Computer Networks

      • Giorgio Giacinto, Fabio Roli, Luca Didaci
      Pages 346-355

    4. Input Space Transformations for Multi-classifier Systems Based on n-tuple Classifiers with Application to Handwriting Recognition

      • K. Sirlantzis, S. Hoque, M. C. Fairhurst
      Pages 356-365

    5. Building Classifier Ensembles for Automatic Sports Classification

      • Edward Jaser, Josef Kittler, William Christmas
      Pages 366-374

    6. Classification of Aircraft Maneuvers for Fault Detection

      • Nikunj C. Oza, Kagan Tumer, Irem Y. Tumer, Edward M. Huff
      Pages 375-384

    7. Solving Problems Two at a Time: Classification of Web Pages Using a Generic Pair-Wise Multiple Classifier System

      • Hassan Alam, Fuad Rahman, Yuliya Tarnikova
      Pages 385-394
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About this book

 

This book constitutes 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

Editors and Affiliations

  • Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, Surrey, UK

    Terry Windeatt

  • Dept. of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy

    Fabio Roli

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