Self-Supervised Learning-Based Time Series Classification via Hierarchical Sparse Convolutional Masked-Autoencoder

Self-Supervised Learning-Based Time Series Classification via Hierarchical Sparse Convolutional Masked-Autoencoder

In recent years, the use of time series analysis has become widespread, prompting researchers to explore methods to improve classification. Time series self-supervised learning has emerged as a significant area of study, aiming to uncover patterns in unlabeled data for richer information. Contrastiv...

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Bibliographic Details
Main Authors: Ting Yu, Kele Xu, Xu Wang, Bo Ding, Dawei Feng
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Time series classification
self-supervised learning
time series pre-training
Online Access:https://ieeexplore.ieee.org/document/10614789/

Internet

https://ieeexplore.ieee.org/document/10614789/

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