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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

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 What’s Wrong with Computer Vision?
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    Chapter 2 Deep Learning in the Wild
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    Chapter 3 Effect of Equality Constraints to Unconstrained Large Margin Distribution Machines
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    Chapter 4 DLL: A Fast Deep Neural Network Library
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    Chapter 5 Selecting Features from Foreign Classes
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    Chapter 6 A Refinement Algorithm for Deep Learning via Error-Driven Propagation of Target Outputs
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    Chapter 7 Combining Deep Learning and Symbolic Processing for Extracting Knowledge from Raw Text
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    Chapter 8 SeNA-CNN: Overcoming Catastrophic Forgetting in Convolutional Neural Networks by Selective Network Augmentation
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    Chapter 9 Classification Uncertainty of Deep Neural Networks Based on Gradient Information
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    Chapter 10 Learning Neural Models for End-to-End Clustering
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    Chapter 11 A $$k$$ -Nearest Neighbor Based Algorithm for Multi-Instance Multi-Label Active Learning
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    Chapter 12 Manifold Learning Regression with Non-stationary Kernels
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    Chapter 13 F-Measure Curves for Visualizing Classifier Performance with Imbalanced Data
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    Chapter 14 Maximum-Likelihood Estimation of Neural Mixture Densities: Model, Algorithm, and Preliminary Experimental Evaluation
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    Chapter 15 Generating Bounding Box Supervision for Semantic Segmentation with Deep Learning
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    Chapter 16 Inductive–Transductive Learning with Graph Neural Networks
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    Chapter 17 Bounded Rational Decision-Making with Adaptive Neural Network Priors
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    Chapter 18 Feature Selection with Rényi Min-Entropy
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    Chapter 19 Extracting Gamma-Ray Information from Images with Convolutional Neural Network Methods on Simulated Cherenkov Telescope Array Data
  21. Altmetric Badge
    Chapter 20 Automatic Hand Sign Recognition: Identify Unusuality Through Latent Cognizance
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    Chapter 21 Cascade of Ordinal Classification and Local Regression for Audio-Based Affect Estimation
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    Chapter 22 Combining Classical and Deep Learning Methods for Twitter Sentiment Analysis
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    Chapter 23 PHoG Features and Kullback-Leibler Divergence Based Ranking Method for Handwriting Recognition
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    Chapter 24 Pattern Recognition Pipeline for Neuroimaging Data
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    Chapter 25 Anomaly Pattern Recognition with Privileged Information for Sensor Fault Detection
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    Chapter 26 Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering
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    Chapter 27 Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps
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    Chapter 28 Video and Audio Data Extraction for Retrieval, Ranking and Recapitulation (VADER $$^3$$ )
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    Chapter 29 ATM Protection Using Embedded Deep Learning Solutions
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    Chapter 30 Object Detection in Floor Plan Images
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    Chapter 31 Historical Handwritten Document Segmentation by Using a Weighted Loss
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
1 blog
twitter
5 X users
patent
2 patents

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
37 Mendeley
Summary Blogs X Patents Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Artificial Neural Networks in Pattern Recognition
Published by
arXiv, November 2018
DOI 10.1007/978-3-319-99978-4
ISBNs
978-3-31-999977-7, 978-3-31-999978-4
Authors

S. Mangano, C. Delgado, M. Bernardos, M. Lallena, J. J. Rodríguez Vázquez

Editors

Pancioni, Luca, Schwenker, Friedhelm, Trentin, Edmondo

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 11%
Student > Ph. D. Student 4 11%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Lecturer 2 5%
Other 6 16%
Unknown 17 46%
Readers by discipline Count As %
Physics and Astronomy 9 24%
Computer Science 7 19%
Engineering 2 5%
Energy 1 3%
Unknown 18 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 13 February 2024.
All research outputs
#2,237,023
of 25,377,790 outputs
Outputs from arXiv
#35,052
of 914,917 outputs
Outputs of similar age
#45,181
of 354,551 outputs
Outputs of similar age from arXiv
#859
of 20,628 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 914,917 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 354,551 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 20,628 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.

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