A Multimodal Sensor-Based Self-Supervised Learning Framework for Low-Noise System State Prediction and Anomaly Detection.

Guo K, Wang J, Lin J, Chen N, Chen H, Zhou Z, Li M

Open source

DOI
10.3390/s26123851
Published
2026 Jun 17
Container
Sensors (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/s26123851,
  title = {A Multimodal Sensor-Based Self-Supervised Learning Framework for Low-Noise System State Prediction and Anomaly Detection.},
  author = {Guo K and Wang J and Lin J and Chen N and Chen H and Zhou Z and Li M},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26123851},
  url = {https://doi.org/10.3390/s26123851}
}

RIS

TY  - JOUR
TI  - A Multimodal Sensor-Based Self-Supervised Learning Framework for Low-Noise System State Prediction and Anomaly Detection.
AU  - Guo K
AU  - Wang J
AU  - Lin J
AU  - Chen N
AU  - Chen H
AU  - Zhou Z
AU  - Li M
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26123851
UR  - https://doi.org/10.3390/s26123851
ER  -

APA

K, G., J, W., J, L., N, C., H, C., Z, Z., & M, L. (2026). A Multimodal Sensor-Based Self-Supervised Learning Framework for Low-Noise System State Prediction and Anomaly Detection.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26123851

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