Multiple Classifier Systems : First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings / / edited by Josef Kittler, Fabio Roli

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2000
• Edizione: 1st ed. 2000.
• Descrizione fisica: 1 online resource (XII, 408 p.)
• Disciplina: 006.3/1
• Soggetto topico: Ensemble learning (Machine learning); Pattern recognition; Artificial intelligence; Optical data processing; Algorithms; Computers; Pattern Recognition; Artificial Intelligence; Image Processing and Computer Vision; Algorithm Analysis and Problem Complexity; Computation by Abstract Devices
• Persona (resp. second.): KittlerJosef; RoliFabio
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Ensemble Methods in Machine Learning -- Experiments with Classifier Combining Rules -- The “Test and Select” Approach to Ensemble Combination -- A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at CEDAR -- Multiple Classifier Combination Methodologies for Different Output Levels -- A Mathematically Rigorous Foundation for Supervised Learning -- Classifier Combinations: Implementations and Theoretical Issues -- Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification -- Complexity of Classification Problems and Comparative Advantages of Combined Classifiers -- Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems -- Combining Fisher Linear Discriminants for Dissimilarity Representations -- A Learning Method of Feature Selection for Rough Classification -- Analysis of a Fusion Method for Combining Marginal Classifiers -- A hybrid projection based and radial basis function architecture -- Combining Multiple Classifiers in Probabilistic Neural Networks -- Supervised Classifier Combination through Generalized Additive Multi-model -- Dynamic Classifier Selection -- Boosting in Linear Discriminant Analysis -- Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination -- Applying Boosting to Similarity Literals for Time Series Classification -- Boosting of Tree-Based Classifiers for Predictive Risk Modeling in GIS -- A New Evaluation Method for Expert Combination in Multi-expert System Designing -- Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems -- Self-Organizing Decomposition of Functions -- Classifier Instability and Partitioning -- A Hierarchical Multiclassifier System for Hyperspectral Data Analysis -- Consensus Based Classification of Multisource Remote Sensing Data -- Combining Parametric and Nonparametric Classifiers for an Unsupervised Updating of Land-Cover Maps -- A Multiple Self-Organizing Map Scheme for Remote Sensing Classification -- Use of Lexicon Density in Evaluating Word Recognizers -- A Multi-expert System for Dynamic Signature Verification -- A Cascaded Multiple Expert System for Verification -- Architecture for Classifier Combination Using Entropy Measures -- Combining Fingerprint Classifiers -- Statistical Sensor Calibration for Fusion of Different Classifiers in a Biometric Person Recognition Framework -- A Modular Neuro-Fuzzy Network for Musical Instruments Classification -- Classifier Combination for Grammar-Guided Sentence Recognition -- Shape Matching and Extraction by an Array of Figure-and-Ground Classifiers.
• Titolo autorizzato: Multiple Classifier Systems
• ISBN: 3-540-45014-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910767550803321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science, . 0302-9743 ; ; 1857