Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification
Learning time-series representations when only unlabeled data or few labeled samples are available can be a challenging task. Recently, contrastive self-supervised learning has shown great improvement in extracting useful representations from unlabeled data via contrasting different augmented views...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 12 vom: 28. Dez., Seite 15604-15618
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| Auteur principal: |
Eldele, Emadeldeen
(Auteur) |
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| Autres auteurs: |
Ragab, Mohamed,
Chen, Zhenghua,
Wu, Min,
Kwoh, Chee-Keong,
Li, Xiaoli,
Guan, Cuntai |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2023
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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