"Artificial Neural Networks in Pattern Recognition" - Information and Links:

Artificial Neural Networks in Pattern Recognition - Info and Reading Options

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

"Artificial Neural Networks in Pattern Recognition" was published by Springer London, Limited in 2008 - Berlin Heidelberg and the language of the book is English.


“Artificial Neural Networks in Pattern Recognition” Metadata:

  • Title: ➤  Artificial Neural Networks in Pattern Recognition
  • Authors:
  • Language: English
  • Publisher: Springer London, Limited
  • Publish Date:
  • Publish Location: Berlin Heidelberg

“Artificial Neural Networks in Pattern Recognition” Subjects and Themes:

Edition Specifications:

  • Pagination: ix, 322

Edition Identifiers:

AI-generated Review of “Artificial Neural Networks in Pattern Recognition”:


"Artificial Neural Networks in Pattern Recognition" Description:

Open Data:

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

Read “Artificial Neural Networks in Pattern Recognition”:

Read “Artificial Neural Networks in Pattern Recognition” by choosing from the options below.

Search for “Artificial Neural Networks in Pattern Recognition” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “Artificial Neural Networks in Pattern Recognition” in Libraries Near You:

Read or borrow “Artificial Neural Networks in Pattern Recognition” from your local library.

Buy “Artificial Neural Networks in Pattern Recognition” online:

Shop for “Artificial Neural Networks in Pattern Recognition” on popular online marketplaces.