Artificial Neural Networks in Pattern Recognition : Third IAPR TC3 Workshop, ANNPR 2008 Paris, France, July 2-4, 2008, Proceedings

Lionel Prevost

ISBN 10: 3540699384 / ISBN 13: 9783540699385

Editore: Springer, Berlin, Springer, 2008

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - TheThirdIAPRTC3WorkshoponArti cialNeuralNetworksinPatternRec- nition, ANNPR 2008, was held at Pierre and Marie Curie University in Paris (France), July 2 4, 2008. The workshop was organized by the Technical C- mittee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 TCs of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy systems, evolutionary computing and arti cial neural networks and their use in various pattern recognition applications. ANNPR 2008 followed the success of the previous workshops: ANNPR 2003 held at the University of Florence (Italy) andANPPR 2006held at ReisensburgCastle, Universityof Ulm (Germany).All the workshops featured a single-track program including both oral sessions and posters with a focus on active participation from every participant. Inrecentyears,the eld ofneuralnetworkshasmaturedconsiderablyinboth methodologyandreal-worldapplications.Asre ectedinthisbook,arti cialn- ral networks in pattern recognition combine many ideas from machine learning, advanced statistics, signal and image processing for solving complex real-world pattern recognition problems. High quality across such a diverse eld of research can only be achieved through a rigorous and selective review process. For this workshop, 57 papers were submitted out of which 29 were selected for inclusion in the proceedings. The oral sessions included 18 papers, while 11 contributions were presented as posters. ANNPR 2008 featured research works in the areas of supervised and unsupervised learning, multiple classi er systems, pattern recognition in signal and image processing, and feature selection.

Codice articolo 9783540699385

Dati bibliografici

• Titolo: Artificial Neural Networks in Pattern Recognition : Third IAPR TC3 Workshop, ANNPR 2008 Paris, France, July 2-4, 2008, Proceedings
• Editore: Springer, Berlin, Springer
• Data di pubblicazione: 2008
• Lingua: Inglese
• ISBN 10: 3540699384
• ISBN 13: 9783540699385
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 156 A x 19 P (millimetri) 235 millimetri di larghezza per 156 millimetri di altezza per 19 millimetri di profondità
• Peso: 516 grammi

Descrizione articolo

Riassunto

This book constitutes the refereed proceedings of the Third TC3 IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008, held in Paris, France, in July 2008. The 18 revised full papers and 11 revised poster papers presented were carefully reviewed and selected from 57 submissions. The papers combine many ideas from machine learning, advanced statistics, signal and image processing for solving complex real-world pattern recognition problems. The papers are organized in topical sections on unsupervised learning, supervised learning, multiple classifiers, applications, and feature selection.

Contenuti

Unsupervised Learning.- Patch Relational Neural Gas – Clustering of Huge Dissimilarity Datasets.- The Block Generative Topographic Mapping.- Kernel k-Means Clustering Applied to Vector Space Embeddings of Graphs.- Probabilistic Models Based on the ?-Sigmoid Distribution.- How Robust Is a Probabilistic Neural VLSI System Against Environmental Noise.- Supervised Learning.- Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis.- Supervised Incremental Learning with the Fuzzy ARTMAP Neural Network.- Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics.- Neural Approximation of Monte Carlo Policy Evaluation Deployed in Connect Four.- Cyclostationary Neural Networks for Air Pollutant Concentration Prediction.- Fuzzy Evolutionary Probabilistic Neural Networks.- Experiments with Supervised Fuzzy LVQ.- A Neural Network Approach to Similarity Learning.- Partial Discriminative Training of Neural Networks for Classification of Overlapping Classes.- Multiple Classifiers.- Boosting Threshold Classifiers for High– Dimensional Data in Functional Genomics.- Decision Fusion on Boosting Ensembles.- The Mixture of Neural Networks as Ensemble Combiner.- Combining Methods for Dynamic Multiple Classifier Systems.- Researching on Multi-net Systems Based on Stacked Generalization.- Applications.- Real-Time Emotion Recognition from Speech Using Echo State Networks.- Sentence Understanding and Learning of New Words with Large-Scale Neural Networks.- Multi-class Vehicle Type Recognition System.- A Bio-inspired Neural Model for Colour Image Segmentation.- Mining Software Aging Patterns by Artificial Neural Networks.- Bayesian Classifiers for Predicting the Outcome of Breast Cancer Preoperative Chemotherapy.- Feature Selection.- Feature Ranking Ensembles for Facial Action Unit Classification.- Texture Classification with Generalized Fourier Descriptors in Dimensionality Reduction Context: An Overview Exploration.- Improving Features Subset Selection Using Genetic Algorithms for Iris Recognition.- Artificial Neural Network Based Automatic Face Model Generation System from Only One Fingerprint.