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Artificial Neural Networks in Pattern Recognition

Third IAPR TC3 Workshop, ANNPR 2008 Paris, France, July 2-4, 2008, Proceedings

Lionel Prevost, Simone Marinai, Friedhelm Schwenker (Herausgeber)

Buch | Softcover

IX, 322 Seiten

2008 | 2008
Springer Berlin (Verlag)
978-3-540-69938-5 (ISBN)

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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.

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.

Erscheint lt. Verlag	25.6.2008
Reihe/Serie	Lecture Notes in Artificial Intelligence
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	IX, 322 p.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	516 g
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
Schlagworte	Artificial Neural Networks • attribute dependence modeling • bayesian classifiers • Bioinformatics • bio-inspired computation • biometrics • Clustering • Computational Intelligence • Data Mining • dimensionality reduction • dynamic classification • face recognition • fingerprint identification • Genetic algorithms • Hardcover, Softcover / Informatik, EDV/Informatik • HC/Informatik, EDV/Informatik • Image Analysis • image classification • Image Segmentation • knowledge management • machine learning • Multiple Classifier Systems • neural network • Object recognition • Pattern classification • pattern recognition • Self-Organizing Maps • Semi-Supervised Learning • software aging • supervised learning • Support Vector Machines • Unsupervised Learning
ISBN-10	3-540-69938-4 / 3540699384
ISBN-13	978-3-540-69938-5 / 9783540699385
Zustand	Neuware