Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition

Convolutional Neural Networks (CNNs) have been subject to extensive attention in the pattern recognition literature due to unprecedented performance in tasks of information extraction from unstructured data. Whereas available methods for supervised training of a CNN with a given network topology are...

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Veröffentlicht in:	Computers in biology and medicine Jg. 120; S. 103723
Hauptverfasser:	Olsson, Alexander E., Björkman, Anders, Antfolk, Christian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.05.2020 Elsevier Limited
Schlagworte:	Algorithms Artificial neural networks Bioinformatics (Computational Biology) Bioinformatik (Beräkningsbiologi) Collating Computer and Information Sciences Computer applications Convolutional neural networks Data- och informationsvetenskap (Datateknik) Deep learning Discriminant analysis Electromyography Embedded systems Evolutionary algorithms Information retrieval Interfaces Internal Medicine Iterative methods Machine learning Medical research Model selection Muscle-computer interfaces Muscles Myoelectric control Myoelectric pattern recognition Myoelectricity Natural Sciences Naturvetenskap Network topologies Neural networks Other Pattern recognition Problem solving Prostheses Unstructured data Myoelectric control Deep learning Model selection Muscle-computer interfaces Machine learning Electromyography Convolutional neural networks Myoelectric pattern recognition
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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