ISM: intra-class similarity mixing for time series augmentation

References

[1] Buntine W . Machine learning after the deep learning revolution. Frontiers of Computer Science, 2020, 14( 6): 146320

[2] Zhang F, Ngo K H, Yang S, Nosratinia A . Transmit correlation diversity: Generalization, new techniques, and improved bounds. IEEE Transactions on Information Theory, 2022, 68( 6): 3841–3869

[3] Wei K, Li T, Huang F, Chen J, He Z . Cancer classification with data augmentation based on generative adversarial networks. Frontiers of Computer Science, 2022, 16( 2): 162601

[4] Ragab M, Eldele E, Tan W L, Foo C S, Chen Z, Wu M, Kwoh C K, Li X . ADATIME: a benchmarking suite for domain adaptation on time series data. ACM Transactions on Knowledge Discovery from Data, 2023, 17( 8): 106

[5] Kim B, Alawami M A, Kim E, Oh S, Park J, Kim H . A comparative study of time series anomaly detection models for industrial control systems. Sensors, 2023, 23( 3): 1310

[6] Li G, Jung J J . Deep learning for anomaly detection in multivariate time series: approaches, applications, and challenges. Information Fusion, 2023, 91: 93–102

[7] Yun S, Han D, Chun S, Oh S J, Yoo Y, Choe J. CutMix: regularization strategy to train strong classifiers with localizable features. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. 2019, 6022−6031

[8] Bellos D, Basham M, Pridmore T, French A P . A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram. Journal of Synchrotron Radiation, 2019, 26( 3): 839–853

[9] Iwana B K, Uchida S. Time series data augmentation for neural networks by time warping with a discriminative teacher. In: Proceedings of the 25th International Conference on Pattern Recognition (ICPR). 2021, 3558−3565

Acknowledgment

This work was supported by the Fundamental Research Funds for the Central Universities (No. 2-9-2022-062).

Competing interests

The authors declare that they have no competing interests or financial conflicts to disclose.

RIGHTS & PERMISSIONS

2024 Higher Education Press