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7. MCS 2007: Prague, Czech Republic
- Michal Haindl
, Josef Kittler, Fabio Roli:
Multiple Classifier Systems, 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings. Lecture Notes in Computer Science 4472, Springer 2007, ISBN 978-3-540-72481-0
Kernel-Based Fusion
- Vadim Mottl, Alexander Tatarchuk, Valentina Sulimova, Olga Krasotkina, Oleg Seredin:
Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion. 1-12 - David Windridge
, Vadim Mottl, Alexander Tatarchuk, Andrey Eliseyev
:
The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition. 13-21 - Wan-Jui Lee, Sergey Verzakov, Robert P. W. Duin:
Kernel Combination Versus Classifier Combination. 22-31 - Stefano Merler, Giuseppe Jurman, Cesare Furlanello
:
Deriving the Kernel from Training Data. 32-41
Applications
- Kai Lienemann, Thomas Plötz, Gernot A. Fink
:
On the Application of SVM-Ensembles Based on Adapted Random Subspace Sampling for Automatic Classification of NMR Data. 42-51 - Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.:
A New HMM-Based Ensemble Generation Method for Numeral Recognition. 52-61 - Sarunas Raudys, Ömer Kaan Baykan, Ahmet Babalik, Vitalij Denisov
, Antanas Andrius Bielskis:
Classifiers Fusion in Recognition of Wheat Varieties. 62-71 - Roman Bertolami, Horst Bunke:
Multiple Classifier Methods for Offline Handwritten Text Line Recognition. 72-81 - Hans Ulrich Christensen, Daniel Ortiz Arroyo
:
Applying Data Fusion Methods to Passage Retrieval in QAS. 82-92 - Tawfik A. Mohamed, Neamat El Gayar
, Amir F. Atiya
:
A Co-training Approach for Time Series Prediction with Missing Data. 93-102 - Shiliang Sun:
An Improved Random Subspace Method and Its Application to EEG Signal Classification. 103-112 - Shiliang Sun:
Ensemble Learning Methods for Classifying EEG Signals. 113-120 - Mohammad Sadeghi, Samaneh Khoshrou, Josef Kittler:
Confidence Based Gating of Colour Features for Face Authentication. 121-130 - Reza Ebrahimpour, Ehsanollah Kabir
, Mohammad Reza Yousefi:
View-Based Eigenspaces with Mixture of Experts for View-Independent Face Recognition. 131-140 - Ángel Serrano, Isaac Martín de Diego
, Cristina Conde, Enrique Cabello
, Li Bai, LinLin Shen:
Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification. 141-150 - Gian Luca Marcialis
, Fabio Roli
:
Serial Fusion of Fingerprint and Face Matchers. 151-160
Boosting
- Lawrence O. Hall, Robert E. Banfield, Kevin W. Bowyer, W. Philip Kegelmeyer:
Boosting Lite - Handling Larger Datasets and Slower Base Classifiers. 161-170 - Julien Meynet, Jean-Philippe Thiran
:
Information Theoretic Combination of Classifiers with Application to AdaBoost. 171-179 - Yijuan Lu, Qi Tian, Thomas S. Huang:
Interactive Boosting for Image Classification. 180-189
Cluster and Graph Ensembles
- Manuele Bicego, Elzbieta Pekalska, Robert P. W. Duin:
Group-Induced Vector Spaces. 190-199 - Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva
:
Selecting Diversifying Heuristics for Cluster Ensembles. 200-209 - Michal Haindl
, Stanislav Mikes:
Unsupervised Texture Segmentation Using Multiple Segmenters Strategy. 210-219 - Kaspar Riesen
, Horst Bunke:
Classifier Ensembles for Vector Space Embedding of Graphs. 220-230 - Jesús Maudes, Juan José Rodríguez, César Ignacio García-Osorio
:
Cascading for Nominal Data. 231-240
Feature Subspace Ensembles
- Mineichi Kudo
, Satoshi Shirai, Hiroshi Tenmoto:
A Combination of Sample Subsets and Feature Subsets in One-Against-Other Classifiers. 241-250 - Joseph DePasquale, Robi Polikar:
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features. 251-260 - Hugo Silva
, Ana L. N. Fred
:
Feature Subspace Ensembles: A Parallel Classifier Combination Scheme Using Feature Selection. 261-270 - Terry Windeatt
, Matthew Prior:
Stopping Criteria for Ensemble-Based Feature Selection. 271-281
Multiple Classifier System Theory
- Pasquale Foggia, Gennaro Percannella
, Carlo Sansone, Mario Vento:
On Rejecting Unreliably Classified Patterns. 282-291 - Battista Biggio, Giorgio Fumera, Fabio Roli
:
Bayesian Analysis of Linear Combiners. 292-301 - Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.:
Applying Pairwise Fusion Matrix on Fusion Functions for Classifier Combination. 302-311 - Samuel Chindaro, Konstantinos Sirlantzis
, Michael C. Fairhurst:
Modelling Multiple-Classifier Relationships Using Bayesian Belief Networks. 312-321 - Shoushan Li, Chengqing Zong
:
Classifier Combining Rules Under Independence Assumptions. 322-332 - Claudio Marrocco, Paolo Simeone, Francesco Tortorella:
Embedding Reject Option in ECOC Through LDPC Codes. 333-343
Intramodal and Multimodal Fusion of Biometric Experts
- Norman Poh, Guillaume Heusch, Josef Kittler:
On Combination of Face Authentication Experts by a Mixture of Quality Dependent Fusion Classifiers. 344-356 - Roberto Tronci
, Giorgio Giacinto, Fabio Roli
:
Index Driven Combination of Multiple Biometric Experts for AUC Maximisation. 357-366 - Krzysztof Kryszczuk, Andrzej Drygajlo:
Q-stack: Uni- and Multimodal Classifier Stacking with Quality Measures. 367-376 - Jonas Richiardi
, Andrzej Drygajlo:
Reliability-Based Voting Schemes Using Modality-Independent Features in Multi-classifier Biometric Authentication. 377-386 - Sergey Tulyakov, Venu Govindaraju
, Chaohong Wu:
Optimal Classifier Combination Rules for Verification and Identification Systems. 387-396
Majority Voting
- Nitesh V. Chawla
, Jared Sylvester:
Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets. 397-406 - Yun Sheng Chung, D. Frank Hsu, Chuan Yi Tang:
On the Diversity-Performance Relationship for Majority Voting in Classifier Ensembles. 407-420 - Hubert Cecotti, Abdel Belaïd:
Hierarchical Behavior Knowledge Space. 421-430
Ensemble Learning
- Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souza Britto Jr.:
A New Dynamic Ensemble Selection Method for Numeral Recognition. 431-439 - Manuela Zanda, Gavin Brown, Giorgio Fumera, Fabio Roli
:
Ensemble Learning in Linearly Combined Classifiers Via Negative Correlation. 440-449 - Juan José Rodríguez, Ludmila I. Kuncheva
:
Naïve Bayes Ensembles with a Random Oracle. 450-458 - Ludmila I. Kuncheva
, Juan José Rodríguez:
An Experimental Study on Rotation Forest Ensembles. 459-468 - Daniel Kanevskiy, Konstantin V. Vorontsov:
Cooperative Coevolutionary Ensemble Learning. 469-478 - Omer Berkman, Nathan Intrator:
Robust Inference in Bayesian Networks with Application to Gene Expression Temporal Data. 479-489 - Michael Muhlbaier, Robi Polikar:
An Ensemble Approach for Incremental Learning in Nonstationary Environments. 490-500
Invited Papers
- Jón Atli Benediktsson, Jocelyn Chanussot, Mathieu Fauvel:
Multiple Classifier Systems in Remote Sensing: From Basics to Recent Developments. 501-512 - Samy Bengio, Johnny Mariéthoz:
Biometric Person Authentication Is a Multiple Classifier Problem. 513-522
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