Applying Deep Learning to Image and IMU Sensor Data for Real-Time Fatigue Recognition in Table Tennis Players.

Sheu YH, Tai TH, Chen TY, Huang CY, Wu SK

DOI: 10.3390/s26206390
Published: 2026 Oct 9
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s26206390,
  title = {Applying Deep Learning to Image and IMU Sensor Data for Real-Time Fatigue Recognition in Table Tennis Players.},
  author = {Sheu YH and Tai TH and Chen TY and Huang CY and Wu SK},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26206390},
  url = {https://doi.org/10.3390/s26206390}
}

RIS

TY  - JOUR
TI  - Applying Deep Learning to Image and IMU Sensor Data for Real-Time Fatigue Recognition in Table Tennis Players.
AU  - Sheu YH
AU  - Tai TH
AU  - Chen TY
AU  - Huang CY
AU  - Wu SK
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26206390
UR  - https://doi.org/10.3390/s26206390
ER  -

APA

YH, S., TH, T., TY, C., CY, H., & SK, W. (2026). Applying Deep Learning to Image and IMU Sensor Data for Real-Time Fatigue Recognition in Table Tennis Players.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26206390

Source records

pubmed · retrieved 2026-11-10T07:37:43.553Z