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Brain informatics : International Conference, BI 2017, Beijing, China, November 16-18, 2017, Proceedings / Yi Zeng, Yong He, Jeanette Hellgren Kotaleski, Maryann Martone, Bo Xu, Hanchuan Peng, Qingming Luo (eds.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 10654. | Lecture notes in computer science. Lecture notes in artificial intelligence. | LNCS sublibrary. SL 7, Artificial intelligence.Publisher: Cham, Switzerland : Springer, 2017Description: 1 online resource (xvi, 336 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319707723
  • 3319707728
Other title:
  • BI 2017
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3/2 23
LOC classification:
  • QA76.87
Online resources:
Contents:
Intro; Preface; Organization; Contents; Cognitive and Computational Foundations of Brain Science; Speech Emotion Recognition Using Local and Global Features; 1 Introduction; 2 Materials and Methods; 2.1 Database; 2.2 Features for Speech Emotion Recognition; 3 Results/Discussion; 3.1 Classification Results for EMODB; 3.2 Classification Results for RAVDESS; 3.3 SFFS; 4 Conclusions; References; Advertisement and Expectation in Lifestyle Changes: A Computational Model; 1 Introduction; 2 Temporal-Causal Modeling; 3 The Computational Model; 3.1 Graphical Representation of the Model.
3.2 Numerical Representations and Parameters4 Simulation Experiments; 4.1 Hypotheses; 4.2 Scenarios and Results; 4.3 Explanation; 5 Conclusion; References; A Computational Cognitive Model of Self-monitoring and Decision Making for Desire Regulation; Abstract; 1 Introduction; 2 Background; 3 Conceptual Representation of the Model; 3.1 Desire Generation and Choosing Actions; 3.2 Self-monitoring and Regulation Strategies; 3.3 Numerical Representation of the Model; 4 Simulation Results; 5 Conclusion; References; Video Category Classification Using Wireless EEG; Abstract; 1 Introduction.
2 Experimental Setup and Data Acquisition Techniques2.1 Demographics of Subjects; 2.2 EEG Recordings; 2.3 Experimental Setup; 3 Experimental Study and Findings; 3.1 Algorithms and Methods; 3.2 Experimental Results; 4 Discussion; 5 Conclusion; References; Learning Music Emotions via Quantum Convolutional Neural Network; 1 Introduction; 2 Related Work on Quantum Information; 3 Quantum Convolutional Neural Network for Music Emotion Analysis; 3.1 Rationale; 3.2 Quantum Convolutional Neural Network; 4 Experiments; 5 Conclusions; References.
Supervised EEG Source Imaging with Graph Regularization in Transformed Domain1 Introduction; 2 Inverse Problem; 3 Graph Regularized EEG Source Imaging in Transformed Domain; 3.1 EEG Source Imaging in Transformed Domain; 3.2 Discriminative Source Reconstruction with Graph Regularization; 4 Optimization with ADMM Algorithm; 5 Numerical Experiment; 6 Conclusion; References; Insula Functional Parcellation from FMRI Data via Improved Artificial Bee-Colony Clustering; 1 Introduction; 2 Related Content; 2.1 Insula Functional Parcellation Based on FMRI Data; 2.2 Artificial Bee Colony (ABC) Algorithm.
3 DABCC Algorithm3.1 Food Source Representation; 3.2 Initialization; 3.3 Self-adaptive Multidimensional Search Mechanism Based on Difference Bias for Employed Bee Search; 3.4 Algorithm Description; 4 Experimental Results and Analysis; 4.1 Data Description and Preprocessing; 4.2 Evaluation Metrics; 4.3 Search Capability; 4.4 Parcellation Results; 4.5 Functional Consistency; 5 Conclusion; References; EEG-Based Emotion Recognition via Fast and Robust Feature Smoothing; 1 Introduction; 2 Related Work; 3 Moving Average Smoothing on Statistical Feature Set; 3.1 Feature Extraction.
Summary: This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2017, held in Beijing, China, in November 2017. The 31 revised full papers were carefully reviewed and selected from 64 submissions. BI addresses the computational, cognitive, physiological, biological, physical, ecological and social perspectives of brain informatics, as well as topics related to mental health and well-being.
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International conference proceedings.

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed November 9, 2017).

This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2017, held in Beijing, China, in November 2017. The 31 revised full papers were carefully reviewed and selected from 64 submissions. BI addresses the computational, cognitive, physiological, biological, physical, ecological and social perspectives of brain informatics, as well as topics related to mental health and well-being.

Intro; Preface; Organization; Contents; Cognitive and Computational Foundations of Brain Science; Speech Emotion Recognition Using Local and Global Features; 1 Introduction; 2 Materials and Methods; 2.1 Database; 2.2 Features for Speech Emotion Recognition; 3 Results/Discussion; 3.1 Classification Results for EMODB; 3.2 Classification Results for RAVDESS; 3.3 SFFS; 4 Conclusions; References; Advertisement and Expectation in Lifestyle Changes: A Computational Model; 1 Introduction; 2 Temporal-Causal Modeling; 3 The Computational Model; 3.1 Graphical Representation of the Model.

3.2 Numerical Representations and Parameters4 Simulation Experiments; 4.1 Hypotheses; 4.2 Scenarios and Results; 4.3 Explanation; 5 Conclusion; References; A Computational Cognitive Model of Self-monitoring and Decision Making for Desire Regulation; Abstract; 1 Introduction; 2 Background; 3 Conceptual Representation of the Model; 3.1 Desire Generation and Choosing Actions; 3.2 Self-monitoring and Regulation Strategies; 3.3 Numerical Representation of the Model; 4 Simulation Results; 5 Conclusion; References; Video Category Classification Using Wireless EEG; Abstract; 1 Introduction.

2 Experimental Setup and Data Acquisition Techniques2.1 Demographics of Subjects; 2.2 EEG Recordings; 2.3 Experimental Setup; 3 Experimental Study and Findings; 3.1 Algorithms and Methods; 3.2 Experimental Results; 4 Discussion; 5 Conclusion; References; Learning Music Emotions via Quantum Convolutional Neural Network; 1 Introduction; 2 Related Work on Quantum Information; 3 Quantum Convolutional Neural Network for Music Emotion Analysis; 3.1 Rationale; 3.2 Quantum Convolutional Neural Network; 4 Experiments; 5 Conclusions; References.

Supervised EEG Source Imaging with Graph Regularization in Transformed Domain1 Introduction; 2 Inverse Problem; 3 Graph Regularized EEG Source Imaging in Transformed Domain; 3.1 EEG Source Imaging in Transformed Domain; 3.2 Discriminative Source Reconstruction with Graph Regularization; 4 Optimization with ADMM Algorithm; 5 Numerical Experiment; 6 Conclusion; References; Insula Functional Parcellation from FMRI Data via Improved Artificial Bee-Colony Clustering; 1 Introduction; 2 Related Content; 2.1 Insula Functional Parcellation Based on FMRI Data; 2.2 Artificial Bee Colony (ABC) Algorithm.

3 DABCC Algorithm3.1 Food Source Representation; 3.2 Initialization; 3.3 Self-adaptive Multidimensional Search Mechanism Based on Difference Bias for Employed Bee Search; 3.4 Algorithm Description; 4 Experimental Results and Analysis; 4.1 Data Description and Preprocessing; 4.2 Evaluation Metrics; 4.3 Search Capability; 4.4 Parcellation Results; 4.5 Functional Consistency; 5 Conclusion; References; EEG-Based Emotion Recognition via Fast and Robust Feature Smoothing; 1 Introduction; 2 Related Work; 3 Moving Average Smoothing on Statistical Feature Set; 3.1 Feature Extraction.

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