Fan Liu
Orcid: 0000-0002-2193-2152Affiliations:
- Northwestern Polytechnical University, School of Computer Science, Xi'an, China
According to our database1,
Fan Liu
authored at least 13 papers
between 2016 and 2023.
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Bibliography
2023
Anomaly Detection in Quasi-Periodic Time Series based on Automatic Data Segmentation and Attentional LSTM-CNN (Extended Abstract).
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023
Proceedings of the 6th International Conference on E-Business, 2023
2022
Anomaly Detection in Quasi-Periodic Time Series Based on Automatic Data Segmentation and Attentional LSTM-CNN.
IEEE Trans. Knowl. Data Eng., 2022
2021
Exploiting feature fusion and long-term context dependencies for simultaneous ECG heartbeat segmentation and classification.
Int. J. Data Sci. Anal., 2021
2019
Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining.
Sensors, 2019
OSA-weigher: an automated computational framework for identifying obstructive sleep apnea based on event phase segmentation.
J. Ambient Intell. Humaniz. Comput., 2019
Arrhythmias Classification by Integrating Stacked Bidirectional LSTM and Two-Dimensional CNN.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
A LSTM and CNN Based Assemble Neural Network Framework for Arrhythmias Classification.
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
2018
Identification of Hypertension by Mining Class Association Rules from Multi-dimensional Features.
Proceedings of the 24th International Conference on Pattern Recognition, 2018
2016
Identifying Obstructive Sleep Apnea by Exploiting Fine-Grained BCG Features Based on Event Phase Segmentation.
Proceedings of the 16th IEEE International Conference on Bioinformatics and Bioengineering, 2016
A light-weight data preprocessing and integrative scheduling framework for health monitoring.
Proceedings of the 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics, 2016