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| Combining pattern recognition modalities at the sensor level via kernel fusion | |
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| The neutral point method for kernel-based combination of disjoint training data in multi-modal pattern recognition | |
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| Kernel combination versus classifier combination | |
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| Deriving the kernel from training data | |
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| On the application of SVM-ensembles based on adapted random subspace sampling for automatic classification of NMR data | |
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| A new HMM-based ensemble generation method for numeral recognition | |
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| Classifiers fusion in recognition of wheat varieties | |
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| Multiple classifier methods for offline handwritten text line recognition | |
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| Applying data fusion methods to passage retrieval in QAS | |
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| A co-training approach for time series prediction with missing data | |
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| An improved random subspace method and its application to EEG signal classification | |
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| Ensemble learning methods for classifying EEG signals | |
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| Confidence based gating of colour features for face authentication | |
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| View-based Eigenspaces with mixture of experts for view-independent face recognition | |
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| Fusion of support vector classifiers for parallel Gabor methods applied to face verification | |
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| Serial fusion of fingerprint and face matchers | |
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| Boosting lite - handling larger datasets and slower base classifiers | |
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| Information theoretic combination of classifiers with application to AdaBoost | |
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| Interactive boosting for image classification | |
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| Group-induced vector spaces | |
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| Selecting diversifying heuristics for cluster ensembles | |
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| Unsupervised texture segmentation using multiple segmenters strategy | |
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| Classifier ensembles for vector space embedding of graphs | |
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| Cascading for nominal data | |
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| A combination of sample subsets and feature subsets in one-against-other classifiers | |
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| Random feature subset selection for ensemble based classification of data with missing features | |
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| Feature subspace ensembles : a parallel classifier combination scheme using feature selection | |
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| Stopping criteria for ensemble-based feature selection | |
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| On rejecting unreliably classified patterns | |
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| Bayesian analysis of linear combiners | |
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| Applying pairwise fusion matrix on fusion functions for classifier combination | |
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| Modelling multiple-classifier relationships using Bayesian belief networks | |
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| Classifier combining rules under independence assumptions | |
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| Embedding reject option in ECOC through LDPC codes | |
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| On combination of face authentication experts by a mixture of quality dependent fusion classifiers | |
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| Index driven combination of multiple biometric experts for AUC maximisation | |
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| Q - stack : uni- and multimodal classifier stacking with quality measures | |
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| Reliability-based voting schemes using modality-independent features in multi-classifier biometric authentication | |
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| Optimal classifier combination rules for verification and identification systems | |
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| Exploiting diversity in ensembles : improving the performance on unbalanced datasets | |
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| On the diversity-performance relationship for majority voting in classifier ensembles | |
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| Hierarchical behavior knowledge space | |
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| A new dynamic ensemble selection method for numeral recognition | |
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| Ensemble learning in linearly combined classifiers via negative correlation | |
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| Naive Bayes ensembles with a random oracle | |
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| An experimental study on rotation forest ensembles | |
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| Cooperative coevolutionary ensemble learning | |
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| Robust inference in Bayesian networks with application to gene expression temporal data | |
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| An ensemble approach for incremental learning in nonstationary environments | |
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| Multiple classifier systems in remote sensing : from basics to recent developments | |
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| Biometric person authentication is a multiple classifier problem | |
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