Skip to main content
Log in

Non-salient region erasure for time series augmentation

  • Letter
  • Published:
Frontiers of Computer Science Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Olson M, Wyner A J, Berk R. Modern neural networks generalize on small data sets. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems. 2018, 3623–3632

  2. Wang J, Wang Z, Li J, Wu J. Multilevel wavelet decomposition network for interpretable time series analysis. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018, 2437–2446

  3. Yang W, Huang H, Zhang Z, Chen X, Huang K, Zhang S. Towards rich feature discovery with class activation maps augmentation for person re-identification. In: Proceedings of 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019, 1389–1398

  4. Wang J, Peng Z, Wang X, Li C, Wu J. Deep fuzzy cognitive maps for interpretable multivariate time series prediction. IEEE Transactions on Fuzzy Systems, 2021, 29(9): 2647–2660

    Article  Google Scholar 

  5. Lee D, Lee S, Yu H. Learnable dynamic temporal pooling for time series classification. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence. 2021, 8288–8296

  6. Chen N, Zhu J, Chen J, Chen T. Dropout training for SVMs with data augmentation. Frontiers of Computer Science, 2018, 12(4): 694–713

    Article  MathSciNet  Google Scholar 

  7. Forestier G, Petitjean F, Dau H A, Webb G I, Keogh E. Generating synthetic time series to augment sparse datasets. In: Proceedings of 2017 IEEE International Conference on Data Mining. 2017, 865–870

  8. 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. 2021, 3558–3565

Download references

Acknowledgements

This work was supported by the National Key Research and Development Program (2018YFB1306000), Ministry of Industry and Information Technology of China (2105-370171-07-02-860873), State Key Lab of Software Development Environment (SKLSDE), and Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaohui Guo.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, P., Guo, X., Shi, B. et al. Non-salient region erasure for time series augmentation. Front. Comput. Sci. 16, 166349 (2022). https://doi.org/10.1007/s11704-022-1765-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11704-022-1765-6

Navigation