Artificial Neural Networks in Pattern Recognition: 4th IAPR TC3 Workshop, ANNPR 2010, Cairo, Egypt, April 11-13, 2010, Proceedings: Lecture Notes in Computer Science, cartea 5998

Supervised Learning.- Pattern Classification Using a Penalized Likelihood Method.- Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis.- Correlation-Based and Causal Feature Selection Analysis for Ensemble Classifiers.- A New Monte Carlo-Based Error Rate Estimator.- Recognition of Sequences of Graphical Patterns.- Maximum Echo-State-Likelihood Networks for Emotion Recognition.- Robustness Analysis of Eleven Linear Classifiers in Extremely High–Dimensional Feature Spaces.- Unsupervised Learning.- Global Coordination Based on Matrix Neural Gas for Dynamic Texture Synthesis.- SIC-Means: A Semi-fuzzy Approach for Clustering Data Streams Using C-Means.- The Mathematics of Divergence Based Online Learning in Vector Quantization.- Cluster Analysis of Cortical Pyramidal Neurons Using SOM.- Parallelized Kernel Patch Clustering.- Visual Pattern Recognition.- Neural Network Cascade for Facial Feature Localization.- A Hidden Markov Model Based Approach for Facial ExpressionRecognition in Image Sequences.- Analysis, Interpretation, and Recognition of Facial Action Units and Expressions Using Neuro-Fuzzy Modeling.- Content-Based Retrieval and Classification of Ultrasound Medical Images of Ovarian Cysts.- Applications.- A Novel Word Spotting Algorithm Using Bidirectional Long Short-Term Memory Neural Networks.- Swarm Based Fuzzy Discriminant Analysis for Multifunction Prosthesis Control.- Bayesian Learning of Generalized Gaussian Mixture Models on Biomedical Images.- Defective Areas Identification in Aircraft Components by Bivariate EMD Analysis of Ultrasound Signals.- Different Regions Identification in Composite Strain-Encoded (C-SENC) Images Using Machine Learning Techniques.- Exploiting Neural Networks to Enhance Trend Forecasting for Hotels Reservations.- VLSI Architecture of the Fuzzy Fingerprint Vault System.- Invited Talk.- Clustering Very Large Dissimilarity Data Sets.

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