Anomaly Detection in Quasi-Periodic Time Series based on Automatic Data Segmentation and Attentional LSTM-CNN (Extended Abstract)

Fan Liu, Xingshe Zhou 0001, Jinli Cao, Zhu Wang 0001, Tianben Wang, Hua Wang, Yanchun Zhang. Anomaly Detection in Quasi-Periodic Time Series based on Automatic Data Segmentation and Attentional LSTM-CNN (Extended Abstract). In 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023. pages 3777-3778, IEEE, 2023. [doi]

@inproceedings{Liu0C0WWZ23,
  title = {Anomaly Detection in Quasi-Periodic Time Series based on Automatic Data Segmentation and Attentional LSTM-CNN (Extended Abstract)},
  author = {Fan Liu and Xingshe Zhou 0001 and Jinli Cao and Zhu Wang 0001 and Tianben Wang and Hua Wang and Yanchun Zhang},
  year = {2023},
  doi = {10.1109/ICDE55515.2023.00315},
  url = {https://doi.org/10.1109/ICDE55515.2023.00315},
  researchr = {https://researchr.org/publication/Liu0C0WWZ23},
  cites = {0},
  citedby = {0},
  pages = {3777-3778},
  booktitle = {39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023},
  publisher = {IEEE},
  isbn = {979-8-3503-2227-9},
}