An empirical survey of data augmentation for time series classification with neural networks

In recent times, deep artificial neural networks have achieved many successes in pattern recognition. Part of this success can be attributed to the reliance on big data to increase generalization. However, in the field of time series recognition, many datasets are often very small. One method of add...

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Veröffentlicht in:PloS one Jg. 16; H. 7; S. e0254841
Hauptverfasser: Iwana, Brian Kenji, Uchida, Seiichi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Public Library of Science 15.07.2021
Public Library of Science (PLoS)
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ISSN:1932-6203, 1932-6203
Online-Zugang:Volltext
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