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ORCID6. MCS 2005: Seaside, CA, USA
- Nikunj C. Oza, Robi Polikar, Josef Kittler, Fabio Roli:
Multiple Classifier Systems, 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings. Lecture Notes in Computer Science 3541, Springer 2005, ISBN 3-540-26306-3
Future Directions
- Fabio Roli
:
Semi-supervised Multiple Classifier Systems: Background and Research Directions. 1-11
Boosting
- Fei Wang, Changshui Zhang, Naijiang Lu:
Boosting GMM and Its Two Applications. 12-21 - Kenji Nishida, Takio Kurita:
Boosting Soft-Margin SVM with Feature Selection for Pedestrian Detection. 22-31 - D. B. Redpath, Katia Lebart:
Observations on Boosting Feature Selection. 32-41 - Qi Tian, Jie Yu, Thomas S. Huang:
Boosting Multiple Classifiers Constructed by Hybrid Discriminant Analysis. 42-52
Combination Methods
- Raymond S. Smith, Terry Windeatt:
Decoding Rules for Error Correcting Output Code Ensembles. 53-63 - Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang:
A Probability Model for Combining Ranks. 64-73 - Norman Poh, Samy Bengio:
EER of Fixed and Trainable Fusion Classifiers: A Theoretical Study with Application to Biometric Authentication Tasks. 74-85 - Ashish Kapoor, Hyungil Ahn, Rosalind W. Picard:
Mixture of Gaussian Processes for Combining Multiple Modalities. 86-96 - Eunju Kim, Jaepil Ko:
Dynamic Classifier Integration Method. 97-107 - Elizabeth Tapia, Esteban Serra, José Carlos González:
Recursive ECOC for Microarray Data Classification. 108-117 - Christian Thiel, Friedhelm Schwenker, Günther Palm:
Using Dempster-Shafer Theory in MCF Systems to Reject Samples. 118-127 - Robin Patenall, David Windridge, Josef Kittler:
Multiple Classifier Fusion Performance in Networked Stochastic Vector Quantisers. 128-135 - Pavel Paclík, Thomas C. W. Landgrebe, David M. J. Tax, Robert P. W. Duin:
On Deriving the Second-Stage Training Set for Trainable Combiners. 136-146 - Sergey Tulyakov, Venu Govindaraju:
Using Independence Assumption to Improve Multimodal Biometric Fusion. 147-155
Design Methods
- Hansheng Lei, Venu Govindaraju:
Half-Against-Half Multi-class Support Vector Machines. 156-164 - Marina Skurichina, Robert P. W. Duin:
Combining Feature Subsets in Feature Selection. 165-175 - Kyosuke Nishida, Koichiro Yamauchi, Takashi Omori:
ACE: Adaptive Classifiers-Ensemble System for Concept-Drifting Environments. 176-185 - Mordechai Gal-Or, Jerrold H. May, William E. Spangler:
Using Decision Tree Models and Diversity Measures in the Selection of Ensemble Classification Models. 186-195 - Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer:
Ensembles of Classifiers from Spatially Disjoint Data. 196-205 - Thomas C. W. Landgrebe, Pavel Paclík, David M. J. Tax, Robert P. W. Duin:
Optimising Two-Stage Recognition Systems. 206-215 - Lei Chen, Mohamed S. Kamel:
Design of Multiple Classifier Systems for Time Series Data. 216-225 - Andreas Heß, Rinat Khoussainov, Nicholas Kushmerick:
Ensemble Learning with Biased Classifiers: The Triskel Algorithm. 226-235 - Hanan Ayad, Mohamed S. Kamel:
Cluster-Based Cumulative Ensembles. 236-245 - Zeki Erdem, Robi Polikar, Fikret S. Gürgen, Nejat Yumusak:
Ensemble of SVMs for Incremental Learning. 246-256
Performance Analysis
- Liying Yang, Zheng Qin:
Design of a New Classifier Simulator. 257-266 - Anand M. Narasimhamurthy:
Evaluation of Diversity Measures for Binary Classifier Ensembles. 267-277 - Kaibo Duan, S. Sathiya Keerthi:
Which Is the Best Multiclass SVM Method? An Empirical Study. 278-285 - Matthew Prior, Terry Windeatt:
Over-Fitting in Ensembles of Neural Network Classifiers Within ECOC Frameworks. 286-295 - Gavin Brown, Jeremy L. Wyatt, Ping Sun:
Between Two Extremes: Examining Decompositions of the Ensemble Objective Function. 296-305 - Rozita A. Dara, Masoud Makrehchi, Mohamed S. Kamel:
Data Partitioning Evaluation Measures for Classifier Ensembles. 306-315 - Giorgio Fumera, Fabio Roli, Alessandra Serrau:
Dynamics of Variance Reduction in Bagging and Other Techniques Based on Randomisation. 316-325 - Michael Muhlbaier, Apostolos Topalis, Robi Polikar:
Ensemble Confidence Estimates Posterior Probability. 326-335
Applications
- Erinija Pranckeviciene, Richard Baumgartner, Ray L. Somorjai:
Using Domain Knowledge for in the Random Subspace Method: Application: Application to the Classification of Biomedical Spectra. 336-345 - Peng Li, Kap Luk Chan, Sheng Fu, Shankar Muthu Krishnan:
An Abnormal ECG Beat Detection Approach for Long-Term Monitoring of Heart Patients Based on Hybrid Kernel Machine Ensemble. 346-355 - Julian Fiérrez-Aguilar, Daniel Garcia-Romero, Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez:
Speaker Verification Using Adapted User-Dependent Multilevel Fusion. 356-365 - Hakan Erdogan, Aytül Erçil, Hazim Kemal Ekenel, S. Y. Bilgin, Ibrahim Eden, Meltem Kirisçi, Hüseyin Abut:
Multi-modal Person Recognition for Vehicular Applications. 366-375 - Piero P. Bonissone, Neil H. W. Eklund, Kai Goebel:
Using an Ensemble of Classifiers to Audit a Production Classifier. 376-386 - Samuel Chindaro, Konstantinos Sirlantzis, Michael C. Fairhurst:
Analysis and Modelling of Diversity Contribution to Ensemble-Based Texture Recognition Performance. 387-396 - Massimo De Santo, Gennaro Percannella, Carlo Sansone, Mario Vento:
Combining Audio-Based and Video-Based Shot Classification Systems for News Videos Segmentation. 397-406 - Nitesh V. Chawla, Kevin W. Bowyer:
Designing Multiple Classifier Systems for Face Recognition. 407-416 - Suju Rajan, Joydeep Ghosh:
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data. 417-427
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