Cargando…
Deep Unsupervised Domain Adaptation with Time Series Sensor Data: A Survey
Sensors are devices that output signals for sensing physical phenomena and are widely used in all aspects of our social production activities. The continuous recording of physical parameters allows effective analysis of the operational status of the monitored system and prediction of unknown risks....
Autores principales: | Shi, Yongjie, Ying, Xianghua, Yang, Jinfa |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371201/ https://www.ncbi.nlm.nih.gov/pubmed/35898010 http://dx.doi.org/10.3390/s22155507 |
Ejemplares similares
-
Unsupervised multi-source domain adaptation with no observable source data
por: Jeon, Hyunsik, et al.
Publicado: (2021) -
Unsupervised Domain Adaptation for Mitigating Sensor Variability and Interspecies Heterogeneity in Animal Activity Recognition
por: Ahn, Seong-Ho, et al.
Publicado: (2023) -
Adaptive Contrastive Learning with Label Consistency for Source Data Free Unsupervised Domain Adaptation
por: Zhao, Xuejun, et al.
Publicado: (2022) -
A hybrid unsupervised—Deep learning tandem for electrooculography time series analysis
por: Stoean, Ruxandra, et al.
Publicado: (2020) -
GANana: Unsupervised Domain Adaptation for Volumetric Regression of Fruit
por: Hartley, Zane K. J., et al.
Publicado: (2021)