Friedhelm Schwenker / Simone Marinai

Artificial Neural Networks in Pattern Recognition

Second IAPR Workshop, ANNPR 2006, Ulm, Germany, August 31-September 2, 2006, Proceedings
Herausgegeben:Schwenker, Friedhelm; Marinai, Simone

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the Second IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2006, held in Ulm, Germany in August/September 2006. The 26 revised papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on unsupervised learning, semi-supervised learning, supervised learning, support vector learning, multiple classifier systems, visual object recognition, and data mining in bioinformatics.

Produktdetails

• Lecture Notes in Computer Science 4087
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 11829898, 978-3-540-37951-5
• 2006
• Seitenzahl: 316
• Erscheinungstermin: 29. August 2006
• Englisch
• Abmessung: 235mm x 155mm x 18mm
• Gewicht: 445g
• ISBN-13: 9783540379515
• ISBN-10: 3540379517
• Artikelnr.: 20946200

Autorenporträt

Friedhelm Schwenker, University of Ulm, Germany / Simone Marinai, University of Florence, Italy

Inhaltsangabe

Unsupervised Learning.- Simple and Effective Connectionist Nonparametric Estimation of Probability Density Functions.- Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition.- Adaptive Feedback Inhibition Improves Pattern Discrimination Learning.- Semi-supervised Learning.- Supervised Batch Neural Gas.- Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes.- On the Effects of Constraints in Semi-supervised Hierarchical Clustering.- A Study of the Robustness of KNN Classifiers Trained Using Soft Labels.- Supervised Learning.- An Experimental Study on Training Radial Basis Functions by Gradient Descent.- A Local Tangent Space Alignment Based Transductive Classification Algorithm.- Incremental Manifold Learning Via Tangent Space Alignment.- A Convolutional Neural Network Tolerant of Synaptic Faults for Low-Power Analog Hardware.- Ammonium Estimation in a Biological Wastewater Plant Using Feedforward Neural Networks.- Support Vector Learning.- Support Vector Regression Using Mahalanobis Kernels.- Incremental Training of Support Vector Machines Using Truncated Hypercones.- Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques.- Multiple Classifier Systems.- Multiple Classifier Systems for Embedded String Patterns.- Multiple Neural Networks for Facial Feature Localization in Orientation-Free Face Images.- Hierarchical Neural Networks Utilising Dempster-Shafer Evidence Theory.- Combining MF Networks: A Comparison Among Statistical Methods and Stacked Generalization.- Visual Object Recognition.- Object Detection and Feature Base Learning with Sparse Convolutional Neural Networks.- Visual Classification of Images by Learning Geometric Appearances Through Boosting.- An Eye Detection System Based on Neural Autoassociators.- Orientation Histograms for Face Recognition.- Data Mining in Bioinformatics.- An Empirical Comparison of Feature Reduction Methods in the Context of Microarray Data Classification.- Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data.- Learning and Feature Selection Using the Set Covering Machine with Data-Dependent Rays on Gene Expression Profiles.