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Artificial Neural Networks in Pattern Recognition

Overview of attention for book
Cover of 'Artificial Neural Networks in Pattern Recognition'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Pattern Classification Using a Penalized Likelihood Method
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    Chapter 2 Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis
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    Chapter 3 Correlation-Based and Causal Feature Selection Analysis for Ensemble Classifiers
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    Chapter 4 A New Monte Carlo-Based Error Rate Estimator
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    Chapter 5 Recognition of Sequences of Graphical Patterns
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    Chapter 6 Maximum Echo-State-Likelihood Networks for Emotion Recognition
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    Chapter 7 Robustness Analysis of Eleven Linear Classifiers in Extremely High–Dimensional Feature Spaces
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    Chapter 8 Global Coordination Based on Matrix Neural Gas for Dynamic Texture Synthesis
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    Chapter 9 SIC-Means: A Semi-fuzzy Approach for Clustering Data Streams Using C-Means
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    Chapter 10 Artificial Neural Networks in Pattern Recognition
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    Chapter 11 Cluster Analysis of Cortical Pyramidal Neurons Using SOM
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    Chapter 12 Parallelized Kernel Patch Clustering
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    Chapter 13 Neural Network Cascade for Facial Feature Localization
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    Chapter 14 A Hidden Markov Model Based Approach for Facial Expression Recognition in Image Sequences
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    Chapter 15 Analysis, Interpretation, and Recognition of Facial Action Units and Expressions Using Neuro-Fuzzy Modeling
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    Chapter 16 Content-Based Retrieval and Classification of Ultrasound Medical Images of Ovarian Cysts
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    Chapter 17 A Novel Word Spotting Algorithm Using Bidirectional Long Short-Term Memory Neural Networks
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    Chapter 18 Swarm Based Fuzzy Discriminant Analysis for Multifunction Prosthesis Control
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    Chapter 19 Bayesian Learning of Generalized Gaussian Mixture Models on Biomedical Images
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    Chapter 20 Defective Areas Identification in Aircraft Components by Bivariate EMD Analysis of Ultrasound Signals
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    Chapter 21 Different Regions Identification in Composite Strain-Encoded (C-SENC) Images Using Machine Learning Techniques
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    Chapter 22 Exploiting Neural Networks to Enhance Trend Forecasting for Hotels Reservations
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    Chapter 23 VLSI Architecture of the Fuzzy Fingerprint Vault System
  25. Altmetric Badge
    Chapter 24 Clustering Very Large Dissimilarity Data Sets
Overall attention for this book and its chapters
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Mentioned by

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Citations

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6 Dimensions

Readers on

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95 Mendeley
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Title
Artificial Neural Networks in Pattern Recognition
Published by
ADS, April 2010
DOI 10.1007/978-3-642-12159-3
ISBNs
978-3-64-212158-6, 978-3-64-212159-3
Editors

Schwenker, Friedhelm, Gayar, Neamat

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 1%
Unknown 94 99%
Readers by discipline Count As %
Energy 1 1%
Unknown 94 99%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 May 2014.
All research outputs
#11,917,241
of 13,441,297 outputs
Outputs from ADS
#18,562
of 19,799 outputs
Outputs of similar age
#236,286
of 271,264 outputs
Outputs of similar age from ADS
#54
of 66 outputs
Altmetric has tracked 13,441,297 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 19,799 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.