Ensemble augmentation for deep neural networks using 1-D time series vibration data
Purpose: Deep Neural Networks (DNNs) typically require enormous labeled training samples to achieve optimum performance. Therefore, numerous forms of data augmentation techniques are employed to compensate for the lack of training samples. Methods: In this paper, a data augmentation technique named...
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Main Authors: | , , , |
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Format: | Article |
Published: |
Springer Nature
2023
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Subjects: | |
Online Access: | http://eprints.utm.my/104991/ http://dx.doi.org/10.1007/s42417-022-00683-w |
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Institution: | Universiti Teknologi Malaysia |