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Label-efficient time series representation learning: A review
Label-efficient time series representation learning, which aims to learn effective
representations with limited labeled data, is crucial for deploying deep learning models in …
representations with limited labeled data, is crucial for deploying deep learning models in …
Cloud-edge test-time adaptation for cross-domain online machinery fault diagnosis via customized contrastive learning
Nowadays offline transfer learning (TL) is the mainstream research for cross-domain
machinery fault diagnosis (MFD). However, the target data is usually collected online by …
machinery fault diagnosis (MFD). However, the target data is usually collected online by …
MDLR: A multi-task disentangled learning representations for unsupervised time series domain adaptation
Abstract Unsupervised Time Series Domain Adaptation (UTSDA) is a method for transferring
information from a labeled source domain to an unlabeled target domain. The majority of …
information from a labeled source domain to an unlabeled target domain. The majority of …
A survey of spatio-temporal eeg data analysis: from models to applications
[HTML][HTML] CLEAR: Multimodal Human Activity Recognition via Contrastive Learning Based Feature Extraction Refinement
M Cao, J Wan, X Gu - Sensors, 2025 - mdpi.com
Human activity recognition (HAR) has become a crucial research area for many
applications, such as Healthcare, surveillance, etc. With the development of artificial …
applications, such as Healthcare, surveillance, etc. With the development of artificial …
[HTML][HTML] A relation-enhanced mean-teacher framework for source-free domain adaptation of object detection
D Tian, C Xu, S Cao - Alexandria Engineering Journal, 2025 - Elsevier
Abstract Source-Free Domain Adaptation Object Detection (SF-DAOD) is a challenging task
in the field of computer vision. This task is used when the source-domain dataset is not …
in the field of computer vision. This task is used when the source-domain dataset is not …
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement
In this paper, we propose a framework for efficient Source-Free Domain Adaptation (SFDA)
in the context of time-series, focusing on enhancing both parameter efficiency and data …
in the context of time-series, focusing on enhancing both parameter efficiency and data …
Fast Online Fault Diagnosis for PMSM Based on Adaptation Model
H Hu, J Gao, X Zhang, X Zhang, Y Qu… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Permanent magnet synchronous motors (PMSMs) are widely used as the key equipment in
devices due to their superior performance, and their health status is closely related to the …
devices due to their superior performance, and their health status is closely related to the …