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Learning Sequential Data with the Help of Linear Systems Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Using Radial Basis Function Neural Networks for Continuous and Discrete Pain Estimation from Bio-physiological Signals

Authors : Mohammadreza Amirian, Markus Kächele, Friedhelm Schwenker

Published in: Artificial Neural Networks in Pattern Recognition

Publisher: Springer International Publishing

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Abstract

In this work we present extensions for Radial Basis Function networks to improve their ability for discrete and continuous pain intensity estimation. Besides proposing a mid-level fusion scheme, the use of standardization and unconventional loss functions are covered. We show that RBF networks can be improved in this way and present extensive experimental validation to support our findings on a multi-modal dataset.

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Metadata
Title
Using Radial Basis Function Neural Networks for Continuous and Discrete Pain Estimation from Bio-physiological Signals
Authors
Mohammadreza Amirian
Markus Kächele
Friedhelm Schwenker
Copyright Year
2016
Book
Artificial Neural Networks in Pattern Recognition

Print ISBN: 978-3-319-46181-6

Electronic ISBN: 978-3-319-46182-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-46182-3_23

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