LightEdu-Net: Noise-Resilient Multimodal Edge Intelligence for Student-State Monitoring in Resource-Limited Environments

Chenjia Huang, Yanli Chen, Bocheng Zhou, Xiuqi Cai, Ziying Zhai, Jiarui Zhang, Yan Zhan

Open source

DOI
10.3390/s25247529
Published
2025-12-11
Container
Sensors
Publisher
MDPI AG
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.3390/s25247529,
  title = {LightEdu-Net: Noise-Resilient Multimodal Edge Intelligence for Student-State Monitoring in Resource-Limited Environments},
  author = {Chenjia Huang and Yanli Chen and Bocheng Zhou and Xiuqi Cai and Ziying Zhai and Jiarui Zhang and Yan Zhan},
  year = {2025},
  journal = {Sensors},
  doi = {10.3390/s25247529},
  url = {https://doi.org/10.3390/s25247529}
}

RIS

TY  - JOUR
TI  - LightEdu-Net: Noise-Resilient Multimodal Edge Intelligence for Student-State Monitoring in Resource-Limited Environments
AU  - Chenjia Huang
AU  - Yanli Chen
AU  - Bocheng Zhou
AU  - Xiuqi Cai
AU  - Ziying Zhai
AU  - Jiarui Zhang
AU  - Yan Zhan
PY  - 2025
JO  - Sensors
DO  - 10.3390/s25247529
UR  - https://doi.org/10.3390/s25247529
ER  - 

APA

Huang, C., Chen, Y., Zhou, B., Cai, X., Zhai, Z., Zhang, J., & Zhan, Y. (2025). LightEdu-Net: Noise-Resilient Multimodal Edge Intelligence for Student-State Monitoring in Resource-Limited Environments. Sensors. https://doi.org/10.3390/s25247529

Source records