Data augmentation for numerical data from manufacturing processes: an overview of techniques and assessment of when which techniques work
Abstract Over the past two decades, machine learning (ML) has transformed manufacturing, particularly in optimizing production and quality control. A significant challenge in ML applications is obtaining sufficient training data, which data augmentation aims to address. While widely applied to image...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-01-01
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| Series: | Industrial Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44244-024-00021-x |
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