A Shapelet Learning Method for Time Series Classification

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) ◽

10.1109/ictai.2016.0071 ◽

2016 ◽

Author(s):

Yi Yang ◽

Qilin Deng ◽

Furao Shen ◽

Jinxi Zhao ◽

Chaomin Luo

Keyword(s):

Time Series ◽

Learning Method ◽

Time Series Classification

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A deep multi-task representation learning method for time series classification and retrieval

Information Sciences ◽

10.1016/j.ins.2020.12.062 ◽

2021 ◽

Vol 555 ◽

pp. 17-32

Author(s):

Ling Chen ◽

Donghui Chen ◽

Fan Yang ◽

Jianling Sun

Keyword(s):

Time Series ◽

Representation Learning ◽

Learning Method ◽

Time Series Classification ◽

Task Representation

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A Reverse Nearest Neighbor Based Active Semi-supervised Learning Method for Multivariate Time Series Classification

Lecture Notes in Computer Science - Database and Expert Systems Applications ◽

10.1007/978-3-319-44403-1_17 ◽

2016 ◽

pp. 272-286 ◽

Author(s):

Yifei Li ◽

Guoliang He ◽

Xuewen Xia ◽

Yuanxiang Li

Keyword(s):

Time Series ◽

Supervised Learning ◽

Nearest Neighbor ◽

Multivariate Time Series ◽

Learning Method ◽

Time Series Classification ◽

Reverse Nearest Neighbor

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Shepard Interpolation Neural Networks with K-Means: A Shallow Learning Method for Time Series Classification

2018 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2018.8489490 ◽

2018 ◽

Author(s):

Kaleb E. Smith ◽

Phillip Williams ◽

Kaylen J. Bryan ◽

Mitchell Solomon ◽

Max Ble ◽

...

Keyword(s):

Neural Networks ◽

Time Series ◽

Learning Method ◽

Time Series Classification

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A nearest neighbor-based active learning method and its application to time series classification

Pattern Recognition Letters ◽

10.1016/j.patrec.2021.03.016 ◽

2021 ◽

Author(s):

Hyukjun Gweon ◽

Hao Yu

Keyword(s):

Time Series ◽

Active Learning ◽

Nearest Neighbor ◽

Learning Method ◽

Time Series Classification ◽

Active Learning Method

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ACTS: An Active Learning Method for Time Series Classification

2017 IEEE 33rd International Conference on Data Engineering (ICDE) ◽

10.1109/icde.2017.68 ◽

2017 ◽

Author(s):

Fengchao Peng ◽

Qiong Luo ◽

Lionel M. Ni

Keyword(s):

Time Series ◽

Active Learning ◽

Learning Method ◽

Time Series Classification ◽

Active Learning Method

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Multiple fault diagnosis for hydraulic systems using Nearest-centroid-with-DBA and Random-Forest-based-time-series-classification

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9189401 ◽

2020 ◽

Author(s):

Zhijie Peng ◽

Ke Zhang ◽

Yi Chai

Keyword(s):

Time Series ◽

Fault Diagnosis ◽

Random Forest ◽

Time Series Classification ◽

Hydraulic Systems ◽

Multiple Fault ◽

Multiple Fault Diagnosis

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A Frequent Pattern Based Time Series Classification Framework

JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY ◽

10.3724/sp.j.1146.2009.00135 ◽

2010 ◽

Vol 32 (2) ◽

pp. 261-266

Author(s):

Li Wan ◽

Jian-xin Liao ◽

Xiao-min Zhu ◽

Ping Ni

Keyword(s):

Time Series ◽

Frequent Pattern ◽

Time Series Classification ◽

Classification Framework

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Uncertain Time Series Classification with Shapelet Transform

2020 International Conference on Data Mining Workshops (ICDMW) ◽

10.1109/icdmw51313.2020.00044 ◽

2020 ◽

Author(s):

Michael Franklin Mbouopda ◽

Engelbert Mephu Nguifo

Keyword(s):

Time Series ◽

Time Series Classification ◽

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Time series classification of radio signal strength for qualitative estimate of UAV motion

Machine Learning with Applications ◽

10.1016/j.mlwa.2021.100027 ◽

2021 ◽

pp. 100027

Author(s):

Samuel Teague ◽

Javaan Chahl

Keyword(s):

Time Series ◽

Radio Signal ◽

Signal Strength ◽

Time Series Classification ◽

Qualitative Estimate

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Meta-Learning For Few-Shot Time Series Classification

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss39084.2020.9441016 ◽

2020 ◽

Author(s):

Sherrie Wang ◽

Marc Ruswurm ◽

Marco Korner ◽

David B. Lobell

Keyword(s):

Time Series ◽

Time Series Classification ◽

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