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Brain-Inspired Computing

Overview of attention for book
Cover of 'Brain-Inspired Computing'

Table of Contents

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    Book Overview
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    Chapter 1 Human Brainnetome Atlas and Its Potential Applications in Brain-Inspired Computing
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    Chapter 2 Workflows for Ultra-High Resolution 3D Models of the Human Brain on Massively Parallel Supercomputers
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    Chapter 3 Towards Large-Scale Fiber Orientation Models of the Brain – Automation and Parallelization of a Seeded Region Growing Segmentation of High-Resolution Brain Section Images
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    Chapter 4 Including Gap Junctions into Distributed Neuronal Network Simulations
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    Chapter 5 Designing Workflows for the Reproducible Analysis of Electrophysiological Data
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    Chapter 6 Finite-Difference Time-Domain Simulation for Three-Dimensional Polarized Light Imaging
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    Chapter 7 Visual Processing in Cortical Architecture from Neuroscience to Neuromorphic Computing
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    Chapter 8 Bio-Inspired Filters for Audio Analysis
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    Chapter 9 Sophisticated LVQ Classification Models - Beyond Accuracy Optimization
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    Chapter 10 Classification of FDG-PET Brain Data by Generalized Matrix Relevance LVQ
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    Chapter 11 A Cephalomorph Real-Time Computer
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    Chapter 12 Towards the Ultimate Display for Neuroscientific Data Analysis
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    Chapter 13 Sentiment Analysis and Affective Computing: Methods and Applications
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    Chapter 14 Deep Representations for Collaborative Robotics
Attention for Chapter 9: Sophisticated LVQ Classification Models - Beyond Accuracy Optimization
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Citations

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Chapter title
Sophisticated LVQ Classification Models - Beyond Accuracy Optimization
Chapter number 9
Book title
Brain-Inspired Computing
Published by
Springer, Cham, July 2015
DOI 10.1007/978-3-319-50862-7_9
Book ISBNs
978-3-31-950861-0, 978-3-31-950862-7
Authors

Thomas Villmann

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Engineering 1 100%

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