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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Vydané v:	IEEE open journal of signal processing Ročník 5; s. 964 - 975
Hlavní autori:	Yu, Ting, Xu, Kele, Wang, Xu, Ding, Bo, Feng, Dawei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Classification Computer architecture Convolution Convolutional neural networks Decoders Decoding Effectiveness Machine learning Self-supervised learning Task analysis Time series Time series analysis Time series classification time series pre-training Transformers
ISSN:	2644-1322, 2644-1322
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