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Self-supervised Learning for Semi-supervised Time Series Classification
Self-supervised learning is a promising new technique for learning representative features in the absence of manual annotations. It is particularly efficient in cases where labeling the training data is expensive and tedious, naturally linking it to the semi-supervised learning paradigm. In this wor...
Uloženo v:
| Vydáno v: | Advances in Knowledge Discovery and Data Mining |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7206263/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47426-3_39 |
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