Evaluate Pseudo Labeling and CNN for Multi-variate Time Series Classification in Low-Data Regimes-Reference-Cited by-同舟云学术

Evaluate Pseudo Labeling and CNN for Multi-variate Time Series Classification in Low-Data Regimes

Published:2021 Issue: Volume: Page:126-137
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Ienco Dino,Pereira-Santos Davi,de Carvalho André C. P. L. F.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-86383-8_10

Reference18 articles.

1. Buitinck, L., et al.: API design for machine learning software: experiences from the scikit-learn project. In: ECML PKDD Workshop: Languages for Data Mining and Machine Learning, pp. 108–122 (2013)

2. Castellanos, M.G., Bergmeir, C., Triguero, I., Rodríguez, Y., Benítez, J.M.: Self-labeling techniques for semi-supervised time series classification: an empirical study. Knowl. Inf. Syst. 55(2), 493–528 (2018)

3. Chen, Y., Hu, B., Keogh, E.J., Batista, G.E.A.P.A.: DTW-D: time series semi-supervised learning from a single example. In: KDD, pp. 383–391. ACM (2013)

4. Fawaz, H.I., Forestier, G., Weber, J., Idoumghar, L., Muller, P.: Deep learning for time series classification: a review. Data Min. Knowl. Discov. 33(4), 917–963 (2019)

5. Frank, J., Mannor, S., Pineau, J., Precup, D.: Time series analysis using geometric template matching. IEEE Trans. Pattern Anal. Mach. Intell. 35(3), 740–754 (2013)

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