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Artificial Neural Networks and Machine Learning – ICANN 2016

Overview of attention for book
Cover of 'Artificial Neural Networks and Machine Learning – ICANN 2016'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Video Description Using Bidirectional Recurrent Neural Networks
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    Chapter 2 Tactile Convolutional Networks for Online Slip and Rotation Detection
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    Chapter 3 DeepPainter: Painter Classification Using Deep Convolutional Autoencoders
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    Chapter 4 Revisiting Deep Convolutional Neural Networks for RGB-D Based Object Recognition
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    Chapter 5 Deep Learning for Emotion Recognition in Faces
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    Chapter 6 Extracting Muscle Synergy Patterns from EMG Data Using Autoencoders
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    Chapter 7 Integration of Unsupervised and Supervised Criteria for Deep Neural Networks Training
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    Chapter 8 Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers
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    Chapter 9 Analysis of Dropout Learning Regarded as Ensemble Learning
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    Chapter 10 The Effects of Regularization on Learning Facial Expressions with Convolutional Neural Networks
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    Chapter 11 DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess
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    Chapter 12 A Convolutional Network Model of the Primate Middle Temporal Area
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    Chapter 13 Pseudo Boosted Deep Belief Network
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    Chapter 14 Keyword Spotting with Convolutional Deep Belief Networks and Dynamic Time Warping
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    Chapter 15 Computational Advantages of Deep Prototype-Based Learning
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    Chapter 16 Deep Convolutional Neural Networks for Classifying Body Constitution
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    Chapter 17 Feature Extractor Based Deep Method to Enhance Online Arabic Handwritten Recognition System
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    Chapter 18 On Higher Order Computations and Synaptic Meta-Plasticity in the Human Brain
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    Chapter 19 Compression of Deep Neural Networks on the Fly
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    Chapter 20 Blind Super-Resolution with Deep Convolutional Neural Networks
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    Chapter 21 DNN-Buddies: A Deep Neural Network-Based Estimation Metric for the Jigsaw Puzzle Problem
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    Chapter 22 A Deep Learning Approach for Hand Posture Recognition from Depth Data
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    Chapter 23 Action Recognition in Surveillance Video Using ConvNets and Motion History Image
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    Chapter 24 Bi-Modal Deep Boltzmann Machine Based Musical Emotion Classification
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    Chapter 25 StreamLeader: A New Stream Clustering Algorithm not Based in Conventional Clustering
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    Chapter 26 Comparison of Methods for Community Detection in Networks
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    Chapter 27 A Robust Evolutionary Optimisation Approach for Parameterising a Neural Mass Model
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    Chapter 28 Kernel Depth Measures for Functional Data with Application to Outlier Detection
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    Chapter 29 Nesterov Acceleration for the SMO Algorithm
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    Chapter 30 Local Reject Option for Deterministic Multi-class SVM
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    Chapter 31 Palmprint Biometric System Modeling by DBC and DLA Methods and Classifying by KNN and SVM Classifiers
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    Chapter 32 Ensemble Models of Learning Vector Quantization Based on Bootstrap Resampling
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    Chapter 33 Cluster Ensembles Optimization Using Coral Reefs Optimization Algorithm
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    Chapter 34 Classification of Photo and Sketch Images Using Convolutional Neural Networks
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    Chapter 35 Day-ahead PV Power Forecast by Hybrid ANN Compared to the Five Parameters Model Estimated by Particle Filter Algorithm
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    Chapter 36 Extended Weighted Nearest Neighbor for Electricity Load Forecasting
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    Chapter 37 Using Reservoir Computing and Trend Information for Short-Term Streamflow Forecasting
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    Chapter 38 Effect of Simultaneous Time Series Prediction with Various Horizons on Prediction Quality at the Example of Electron Flux in the Outer Radiation Belt of the Earth
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    Chapter 39 A Time Series Forecasting Model Based on Deep Learning Integrated Algorithm with Stacked Autoencoders and SVR for FX Prediction
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    Chapter 40 Multivariate Dynamic Kernels for Financial Time Series Forecasting
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    Chapter 41 Symbolic Association Using Parallel Multilayer Perceptron
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    Chapter 42 Solution of an Inverse Problem in Raman Spectroscopy of Multi-component Solutions of Inorganic Salts by Artificial Neural Networks
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    Chapter 43 Sound Recognition System Using Spiking and MLP Neural Networks
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    Chapter 44 Using Machine Learning Techniques to Recover Prismatic Cirrus Ice Crystal Size from 2-Dimensional Light Scattering Patterns
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    Chapter 45 25 Years of CNNs: Can We Compare to Human Abstraction Capabilities?
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    Chapter 46 A Combination Method for Reducing Dimensionality in Large Datasets
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    Chapter 47 Two-Class with Oversampling Versus One-Class Classification for Microarray Datasets
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    Chapter 48 Polar Sine Based Siamese Neural Network for Gesture Recognition
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    Chapter 49 Day Types Identification of Algerian Electricity Load Using an Image Based Two-Stage Approach
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    Chapter 50 SMS Spam Filtering Using Probabilistic Topic Modelling and Stacked Denoising Autoencoder
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    Chapter 51 Improving MDLSTM for Offline Arabic Handwriting Recognition Using Dropout at Different Positions
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    Chapter 52 A Neural Network Model for Solving the Feature Correspondence Problem
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    Chapter 53 The Performance of a Biologically Plausible Model of Visual Attention to Localize Objects in a Virtual Reality
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    Chapter 54 Pose-Invariant Object Recognition for Event-Based Vision with Slow-ELM
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    Chapter 55 Learning V4 Curvature Cell Populations from Sparse Endstopped Cells
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    Chapter 56 Recognition of Transitive Actions with Hierarchical Neural Network Learning
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    Chapter 57 Rotation-Invariant Restricted Boltzmann Machine Using Shared Gradient Filters
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    Chapter 58 Improving Robustness of Slow Feature Analysis Based Localization Using Loop Closure Events
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    Chapter 59 Self-Organizing Map for the Curvature-Constrained Traveling Salesman Problem
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    Chapter 60 Non-negative Kernel Sparse Coding for the Analysis of Motion Data
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    Chapter 61 Effect of Neural Controller on Adaptive Cruise Control
  63. Altmetric Badge
    Chapter 62 Intelligent Speech-Based Interactive Communication Between Mobile Cranes and Their Human Operators
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

1 blog
67 tweeters
4 Facebook pages
3 Google+ users
1 Redditor


3 Dimensions

Readers on

104 Mendeley
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Artificial Neural Networks and Machine Learning – ICANN 2016
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-44781-0
978-3-31-944780-3, 978-3-31-944781-0

Alessandro E.P. Villa, Paolo Masulli, Antonio Javier Pons Rivero

Twitter Demographics

The data shown below were collected from the profiles of 67 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 5%
Researcher 4 4%
Student > Bachelor 2 2%
Student > Ph. D. Student 1 <1%
Lecturer 1 <1%
Other 1 <1%
Unknown 90 87%
Readers by discipline Count As %
Computer Science 6 6%
Engineering 3 3%
Mathematics 2 2%
Materials Science 1 <1%
Economics, Econometrics and Finance 1 <1%
Other 0 0%
Unknown 91 88%

Attention Score in Context

This research output has an Altmetric Attention Score of 46. 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 06 July 2020.
All research outputs
of 15,565,939 outputs
Outputs from Lecture notes in computer science
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Outputs of similar age
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Outputs of similar age from Lecture notes in computer science
of 78 outputs
Altmetric has tracked 15,565,939 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,583 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 99% 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 265,168 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 78 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 94% of its contemporaries.