Image analysis and processing : ICIAP 2005, 13th international conference, Cagliari, Italy, September 6-8, 2005 : proceedings / / Fabio Roli, Sergio Vitulano (eds.) |
Edizione | [1st ed. 2005.] |
Pubbl/distr/stampa | Berlin ; ; New York, : Springer, 2005 |
Descrizione fisica | 1 online resource (XXIV, 1219 p.) |
Disciplina | 006.4 |
Altri autori (Persone) |
RoliFabio <1962->
VitulanoSergio |
Collana | Lecture notes in computer science |
Soggetto topico | Image processing |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Invited Papers -- Pattern Recognition for Computer Network Security -- Computer Vision for Augmented Reality and Augmented Environments -- Low and Middle Level Processing -- Image Segmentation -- Feature Extraction and Image Analysis -- Graphs -- Shape and Motion -- Image Modelling and Computer Graphics -- Image Communication, Coding and Security -- Computer Architectures, Technologies and Tools -- Multimedia Data Bases -- Video Processing and Analysis -- Pattern Classification and Learning -- Stereo Vision -- 3D Vision -- Medical Applications -- Biometrics -- Applications. |
Altri titoli varianti | ICIAP 2005 |
Record Nr. | UNINA-9910485028803321 |
Berlin ; ; New York, : Springer, 2005 | ||
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Lo trovi qui: Univ. Federico II | ||
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Multiple classifier systems : 9th international workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010 : proceedings / / Neamat El Gayar, Josef Kittler, Fabio Roli (eds.) |
Edizione | [1st ed. 2010.] |
Pubbl/distr/stampa | Berlin, : Springer, c2010 |
Descrizione fisica | 1 online resource (X, 328 p. 77 illus.) |
Disciplina | 006.3 |
Altri autori (Persone) |
El GayarNeamat
KittlerJosef <1946-> RoliFabio <1962-> |
Collana |
Lecture notes in computer science
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics |
Soggetto topico |
Machine learning
Neural networks (Computer science) Pattern perception |
ISBN |
1-280-38597-9
9786613563897 3-642-12127-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Classifier Ensembles(I) -- Weighted Bagging for Graph Based One-Class Classifiers -- Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers -- New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization -- Incremental Learning of New Classes in Unbalanced Datasets: Learn?+?+?.UDNC -- Tomographic Considerations in Ensemble Bias/Variance Decomposition -- Choosing Parameters for Random Subspace Ensembles for fMRI Classification -- Classifier Ensembles(II) -- An Experimental Study on Ensembles of Functional Trees -- Multiple Classifier Systems under Attack -- SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning -- Unsupervised Change-Detection in Retinal Images by a Multiple-Classifier Approach -- A Double Pruning Algorithm for Classification Ensembles -- Estimation of the Number of Clusters Using Multiple Clustering Validity Indices -- Classifier Diversity -- “Good” and “Bad” Diversity in Majority Vote Ensembles -- Multi-information Ensemble Diversity -- Classifier Selection -- Dynamic Selection of Ensembles of Classifiers Using Contextual Information -- Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems -- Combining Multiple Kernels -- A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities -- Combining Multiple Kernels by Augmenting the Kernel Matrix -- Boosting and Bootstrapping -- Class-Separability Weighting and Bootstrapping in Error Correcting Output Code Ensembles -- Boosted Geometry-Based Ensembles -- Online Non-stationary Boosting -- Handwriting Recognition -- Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting -- Combining Committee-Based Semi-supervised and Active Learning and Its Application to Handwritten Digits Recognition -- Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition -- Applications -- Forecast Combination Strategies for Handling Structural Breaks for Time Series Forecasting -- A Multiple Classifier System for Classification of LIDAR Remote Sensing Data Using Multi-class SVM -- A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation -- A Multi-objective Sequential Ensemble for Cluster Structure Analysis and Visualization and Application to Gene Expression -- Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells -- An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction -- Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network -- Invited Papers -- Some Thoughts at the Interface of Ensemble Methods and Feature Selection -- Multiple Classifier Systems for the Recogonition of Human Emotions -- Erratum -- Erratum. |
Altri titoli varianti | MCS 2010 |
Record Nr. | UNINA-9910484600003321 |
Berlin, : Springer, c2010 | ||
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Lo trovi qui: Univ. Federico II | ||
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Multiple classifier systems : 7th international workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007 : proceedings / / Michal Haindl, Josef Kittler, Fabio Roli (editors) |
Edizione | [1st ed. 2007.] |
Pubbl/distr/stampa | Berlin ; ; Heidelberg ; ; New York : , : Springer, , [2007] |
Descrizione fisica | 1 online resource (534 p.) |
Disciplina | 006.31 |
Collana | Lecture notes in computer science |
Soggetto topico | Machine learning |
ISBN |
1-280-94918-X
9786610949182 3-540-72523-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Kernel-Based Fusion -- Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion -- The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition -- Kernel Combination Versus Classifier Combination -- Deriving the Kernel from Training Data -- Applications -- On the Application of SVM-Ensembles Based on Adapted Random Subspace Sampling for Automatic Classification of NMR Data -- A New HMM-Based Ensemble Generation Method for Numeral Recognition -- Classifiers Fusion in Recognition of Wheat Varieties -- Multiple Classifier Methods for Offline Handwritten Text Line Recognition -- Applying Data Fusion Methods to Passage Retrieval in QAS -- A Co-training Approach for Time Series Prediction with Missing Data -- An Improved Random Subspace Method and Its Application to EEG Signal Classification -- Ensemble Learning Methods for Classifying EEG Signals -- Confidence Based Gating of Colour Features for Face Authentication -- View-Based Eigenspaces with Mixture of Experts for View-Independent Face Recognition -- Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification -- Serial Fusion of Fingerprint and Face Matchers -- Boosting -- Boosting Lite – Handling Larger Datasets and Slower Base Classifiers -- Information Theoretic Combination of Classifiers with Application to AdaBoost -- Interactive Boosting for Image Classification -- Cluster and Graph Ensembles -- Group-Induced Vector Spaces -- Selecting Diversifying Heuristics for Cluster Ensembles -- Unsupervised Texture Segmentation Using Multiple Segmenters Strategy -- Classifier Ensembles for Vector Space Embedding of Graphs -- Cascading for Nominal Data -- Feature Subspace Ensembles -- A Combination of Sample Subsets and Feature Subsets in One-Against-Other Classifiers -- Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features -- Feature Subspace Ensembles: A Parallel Classifier Combination Scheme Using Feature Selection -- Stopping Criteria for Ensemble-Based Feature Selection -- Multiple Classifier System Theory -- On Rejecting Unreliably Classified Patterns -- Bayesian Analysis of Linear Combiners -- Applying Pairwise Fusion Matrix on Fusion Functions for Classifier Combination -- Modelling Multiple-Classifier Relationships Using Bayesian Belief Networks -- Classifier Combining Rules Under Independence Assumptions -- Embedding Reject Option in ECOC Through LDPC Codes -- Intramodal and Multimodal Fusion of Biometric Experts -- On Combination of Face Authentication Experts by a Mixture of Quality Dependent Fusion Classifiers -- Index Driven Combination of Multiple Biometric Experts for AUC Maximisation -- Q???stack: Uni- and Multimodal Classifier Stacking with Quality Measures -- Reliability-Based Voting Schemes Using Modality-Independent Features in Multi-classifier Biometric Authentication -- Optimal Classifier Combination Rules for Verification and Identification Systems -- Majority Voting -- Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets -- On the Diversity-Performance Relationship for Majority Voting in Classifier Ensembles -- Hierarchical Behavior Knowledge Space -- Ensemble Learning -- A New Dynamic Ensemble Selection Method for Numeral Recognition -- Ensemble Learning in Linearly Combined Classifiers Via Negative Correlation -- Naïve Bayes Ensembles with a Random Oracle -- An Experimental Study on Rotation Forest Ensembles -- Cooperative Coevolutionary Ensemble Learning -- Robust Inference in Bayesian Networks with Application to Gene Expression Temporal Data -- An Ensemble Approach for Incremental Learning in Nonstationary Environments -- Invited Papers -- Multiple Classifier Systems in Remote Sensing: From Basics to Recent Developments -- Biometric Person Authentication Is a Multiple Classifier Problem. |
Record Nr. | UNINA-9910483577703321 |
Berlin ; ; Heidelberg ; ; New York : , : Springer, , [2007] | ||
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Lo trovi qui: Univ. Federico II | ||
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Multiple classifier systems : 7th international workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007 : proceedings / / Michal Haindl, Josef Kittler, Fabio Roli (editors) |
Edizione | [1st ed. 2007.] |
Pubbl/distr/stampa | Berlin ; ; Heidelberg ; ; New York : , : Springer, , [2007] |
Descrizione fisica | 1 online resource (534 p.) |
Disciplina | 006.31 |
Collana | Lecture notes in computer science |
Soggetto topico | Machine learning |
ISBN |
1-280-94918-X
9786610949182 3-540-72523-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Kernel-Based Fusion -- Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion -- The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition -- Kernel Combination Versus Classifier Combination -- Deriving the Kernel from Training Data -- Applications -- On the Application of SVM-Ensembles Based on Adapted Random Subspace Sampling for Automatic Classification of NMR Data -- A New HMM-Based Ensemble Generation Method for Numeral Recognition -- Classifiers Fusion in Recognition of Wheat Varieties -- Multiple Classifier Methods for Offline Handwritten Text Line Recognition -- Applying Data Fusion Methods to Passage Retrieval in QAS -- A Co-training Approach for Time Series Prediction with Missing Data -- An Improved Random Subspace Method and Its Application to EEG Signal Classification -- Ensemble Learning Methods for Classifying EEG Signals -- Confidence Based Gating of Colour Features for Face Authentication -- View-Based Eigenspaces with Mixture of Experts for View-Independent Face Recognition -- Fusion of Support Vector Classifiers for Parallel Gabor Methods Applied to Face Verification -- Serial Fusion of Fingerprint and Face Matchers -- Boosting -- Boosting Lite – Handling Larger Datasets and Slower Base Classifiers -- Information Theoretic Combination of Classifiers with Application to AdaBoost -- Interactive Boosting for Image Classification -- Cluster and Graph Ensembles -- Group-Induced Vector Spaces -- Selecting Diversifying Heuristics for Cluster Ensembles -- Unsupervised Texture Segmentation Using Multiple Segmenters Strategy -- Classifier Ensembles for Vector Space Embedding of Graphs -- Cascading for Nominal Data -- Feature Subspace Ensembles -- A Combination of Sample Subsets and Feature Subsets in One-Against-Other Classifiers -- Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features -- Feature Subspace Ensembles: A Parallel Classifier Combination Scheme Using Feature Selection -- Stopping Criteria for Ensemble-Based Feature Selection -- Multiple Classifier System Theory -- On Rejecting Unreliably Classified Patterns -- Bayesian Analysis of Linear Combiners -- Applying Pairwise Fusion Matrix on Fusion Functions for Classifier Combination -- Modelling Multiple-Classifier Relationships Using Bayesian Belief Networks -- Classifier Combining Rules Under Independence Assumptions -- Embedding Reject Option in ECOC Through LDPC Codes -- Intramodal and Multimodal Fusion of Biometric Experts -- On Combination of Face Authentication Experts by a Mixture of Quality Dependent Fusion Classifiers -- Index Driven Combination of Multiple Biometric Experts for AUC Maximisation -- Q???stack: Uni- and Multimodal Classifier Stacking with Quality Measures -- Reliability-Based Voting Schemes Using Modality-Independent Features in Multi-classifier Biometric Authentication -- Optimal Classifier Combination Rules for Verification and Identification Systems -- Majority Voting -- Exploiting Diversity in Ensembles: Improving the Performance on Unbalanced Datasets -- On the Diversity-Performance Relationship for Majority Voting in Classifier Ensembles -- Hierarchical Behavior Knowledge Space -- Ensemble Learning -- A New Dynamic Ensemble Selection Method for Numeral Recognition -- Ensemble Learning in Linearly Combined Classifiers Via Negative Correlation -- Naïve Bayes Ensembles with a Random Oracle -- An Experimental Study on Rotation Forest Ensembles -- Cooperative Coevolutionary Ensemble Learning -- Robust Inference in Bayesian Networks with Application to Gene Expression Temporal Data -- An Ensemble Approach for Incremental Learning in Nonstationary Environments -- Invited Papers -- Multiple Classifier Systems in Remote Sensing: From Basics to Recent Developments -- Biometric Person Authentication Is a Multiple Classifier Problem. |
Record Nr. | UNISA-996466261203316 |
Berlin ; ; Heidelberg ; ; New York : , : Springer, , [2007] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Multiple classifier systems : 8th international workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009: proceedings / / Jon Atli Benediktsson, Josef Kittler, Fabio Rolio (eds.) |
Edizione | [1st ed. 2009.] |
Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2007 |
Descrizione fisica | 1 online resource (XI, 540 p.) |
Disciplina | 006.4 |
Altri autori (Persone) |
Jon Atli Benediktsson
KittlerJosef <1946-> RoliFabio <1962-> |
Collana | Lecture notes in computer science |
Soggetto topico |
Machine learning
Neural networks (Computer science) Pattern perception |
ISBN | 3-642-02326-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | ECOC, Boosting and Bagging -- The Bias Variance Trade-Off in Bootstrapped Error Correcting Output Code Ensembles -- Recoding Error-Correcting Output Codes -- Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting -- Multi-class Boosting with Class Hierarchies -- MCS in Remote Sensing -- Hybrid Hierarchical Classifiers for Hyperspectral Data Analysis -- Multiple Classifier Combination for Hyperspectral Remote Sensing Image Classification -- Ensemble Strategies for Classifying Hyperspectral Remote Sensing Data -- Unbalanced Data and Decision Templates -- Optimal Mean-Precision Classifier -- A Multiple Expert Approach to the Class Imbalance Problem Using Inverse Random under Sampling -- Decision Templates Based RBF Network for Tree-Structured Multiple Classifier Fusion -- Stacked Generalization and Active Learning -- Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors -- Regularized Linear Models in Stacked Generalization -- Active Grading Ensembles for Learning Visual Quality Control from Multiple Humans -- Multiple Classifier Systems for Adversarial Classification Tasks -- Concept Drift, Missing Values and Random Forest -- Incremental Learning of Variable Rate Concept Drift -- Semi-supervised Co-update of Multiple Matchers -- Handling Multimodal Information Fusion with Missing Observations Using the Neutral Point Substitution Method -- Influence of Hyperparameters on Random Forest Accuracy -- SVM Ensembles -- Ensembles of One Class Support Vector Machines -- Disturbing Neighbors Ensembles for Linear SVM -- Fusion of Graphs, Concepts and Categorical Data -- A Labelled Graph Based Multiple Classifier System -- Cluster Ensembles Based on Vector Space Embeddings of Graphs -- Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data -- True Path Rule Hierarchical Ensembles -- Clustering -- A Study of Semi-supervised Generative Ensembles -- Hierarchical Ensemble Support Cluster Machine -- Multi-scale Stacked Sequential Learning -- Unsupervised Hierarchical Weighted Multi-segmenter -- Ant Clustering Using Ensembles of Partitions -- Classifier and Feature Selection -- Selective Ensemble under Regularization Framework -- Criteria Ensembles in Feature Selection -- Network Protocol Verification by a Classifier Selection Ensemble -- Supervised Selective Combining Pattern Recognition Modalities and Its Application to Signature Verification by Fusing On-Line and Off-Line Kernels -- Theory of MCS -- Improved Uniformity Enforcement in Stochastic Discrimination -- An Information Theoretic Perspective on Multiple Classifier Systems -- Constraints in Weighted Averaging -- FaSS: Ensembles for Stable Learners -- MCS Methods and Applications -- Classifying Remote Sensing Data with Support Vector Machines and Imbalanced Training Data -- Terrain Segmentation with On-Line Mixtures of Experts for Autonomous Robot Navigation -- Consistency Measure of Multiple Classifiers for Land Cover Classification by Remote Sensing Image -- Target Identification from High Resolution Remote Sensing Image by Combining Multiple Classifiers -- Neural Network Optimization for Combinations in Identification Systems -- MLP, Gaussian Processes and Negative Correlation Learning for Time Series Prediction -- Diversity-Based Classifier Selection for Adaptive Object Tracking -- Ensemble Based Data Fusion for Gene Function Prediction -- A Cascade Multiple Classifier System for Document Categorization -- Maximum Membership Scale Selection -- An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets -- A Study of Random Linear Oracle Ensembles -- Stacking for Ensembles of Local Experts in Metabonomic Applications -- Boosting Support Vector Machines Successfully -- Invited Papers -- Manifold Learning for Multi-classifier Systems via Ensembles -- When Semi-supervised Learning Meets Ensemble Learning. |
Altri titoli varianti | MCS 2007 |
Record Nr. | UNINA-9910483351103321 |
Berlin ; ; New York, : Springer, c2007 | ||
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Lo trovi qui: Univ. Federico II | ||
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