Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.
- DOI
- 10.3390/s21134550
- Published
- 2021 Jul 2
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s21134550,
title = {Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.},
author = {Brumann C and Kukuk M and Reinsberger C},
year = {2021},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s21134550},
url = {https://doi.org/10.3390/s21134550}
}RIS
TY - JOUR TI - Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash. AU - Brumann C AU - Kukuk M AU - Reinsberger C PY - 2021 JO - Sensors (Basel, Switzerland) DO - 10.3390/s21134550 UR - https://doi.org/10.3390/s21134550 ER -
APA
C, B., M, K., & C, R. (2021). Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s21134550
Source records
- pubmed · retrieved 2026-09-25T01:42:40.392Z