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Advances in Brain Inspired Cognitive Systems

Overview of attention for book
Cover of 'Advances in Brain Inspired Cognitive Systems'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 An Improved Recurrent Network for Online Equality-Constrained Quadratic Programming
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    Chapter 2 Towards Robot Self-consciousness (I): Brain-Inspired Robot Mirror Neuron System Model and Its Application in Mirror Self-recognition
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    Chapter 3 Implementation of EEG Emotion Recognition System Based on Hierarchical Convolutional Neural Networks
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    Chapter 4 Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test
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    Chapter 5 Decoding Visual Stimuli in Human Brain by Using Anatomical Pattern Analysis on fMRI Images
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    Chapter 6 An Investigation of Machine Learning and Neural Computation Paradigms in the Design of Clinical Decision Support Systems (CDSSs)
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    Chapter 7 A Retina Inspired Model for High Dynamic Range Image Rendering
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    Chapter 8 Autoencoders with Drop Strategy
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    Chapter 9 Detecting Rare Visual and Auditory Events from EEG Using Pairwise-Comparison Neural Networks
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    Chapter 10 Compressing Deep Neural Network for Facial Landmarks Detection
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    Chapter 11 Learning Optimal Seeds for Salient Object Detection
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    Chapter 12 A Spiking Neural Network Based Autonomous Reinforcement Learning Model and Its Application in Decision Making
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    Chapter 13 Classification of Spatiotemporal Events Based on Random Forest
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    Chapter 14 Visual Attention Model with a Novel Learning Strategy and Its Application to Target Detection from SAR Images
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    Chapter 15 Modified Cat Swarm Optimization for Clustering
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    Chapter 16 Deep and Sparse Learning in Speech and Language Processing: An Overview
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    Chapter 17 Time-Course EEG Spectrum Evidence for Music Key Perception and Emotional Effects
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    Chapter 18 A Possible Neural Circuit for Decision Making and Its Learning Process
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    Chapter 19 A SVM-Based EEG Signal Analysis: An Auxiliary Therapy for Tinnitus
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    Chapter 20 Passive BCI Based on Sustained Attention Detection: An fNIRS Study
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    Chapter 21 Incremental Learning Vector Quantization for Character Recognition with Local Style Consistency
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    Chapter 22 A Novel Fully Automated Liver and HCC Tumor Segmentation System Using Morphological Operations
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    Chapter 23 A New Biologically-Inspired Analytical Worm Propagation Model for Mobile Unstructured Peer-to-Peer Networks
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    Chapter 24 EEG Brain Functional Connectivity Dynamic Evolution Model: A Study via Wavelet Coherence
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    Chapter 25 Predicting Insulin Resistance in Children Using a Machine-Learning-Based Clinical Decision Support System
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    Chapter 26 An Ontological Framework of Semantic Learner Profile in an E-Learning System
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    Chapter 27 Incremental PCANet: A Lifelong Learning Framework to Achieve the Plasticity of both Feature and Classifier Constructions
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    Chapter 28 PerSent: A Freely Available Persian Sentiment Lexicon
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    Chapter 29 Low-Rank Image Set Representation and Classification
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    Chapter 30 A Data Driven Approach to Audiovisual Speech Mapping
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    Chapter 31 Continuous Time Recurrent Neural Network Model of Recurrent Collaterals in the Hippocampus CA3 Region
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    Chapter 32 Sparse-Network Based Framework for Detecting the Overlapping Community Structure of Brain Functional Network
Attention for Chapter 4: Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test
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Mentioned by

3 tweeters

Readers on

13 Mendeley
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Chapter title
Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test
Chapter number 4
Book title
Advances in Brain Inspired Cognitive Systems
Published in
Lecture notes in computer science, November 2016
DOI 10.1007/978-3-319-49685-6_4
Book ISBNs
978-3-31-949684-9, 978-3-31-949685-6

Qixin Wang, Tianyi Luo, Dong Wang


Cheng-Lin Liu, Amir Hussain, Bin Luo, Kay Chen Tan, Yi Zeng, Zhaoxiang Zhang

Twitter Demographics

The data shown below were collected from the profiles of 3 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 31%
Student > Bachelor 2 15%
Researcher 2 15%
Student > Ph. D. Student 2 15%
Other 1 8%
Other 1 8%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 7 54%
Mathematics 1 8%
Business, Management and Accounting 1 8%
Social Sciences 1 8%
Materials Science 1 8%
Other 0 0%
Unknown 2 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 15 March 2017.
All research outputs
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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 234 outputs
Altmetric has tracked 13,978,928 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,430 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 47th percentile – i.e., 47% of its peers scored the same or lower than it.
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 374,133 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 234 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.