The Devil is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection

Hugues Moreau, Andrea Vassilev, Liming Chen

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DOI: 10.1109/tits.2021.3110949
Published: 2022-08
Container: IEEE Transactions on Intelligent Transportation Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1109/tits.2021.3110949,
  title = {The Devil is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection},
  author = {Hugues Moreau and Andrea Vassilev and Liming Chen},
  year = {2022},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  doi = {10.1109/tits.2021.3110949},
  url = {https://doi.org/10.1109/tits.2021.3110949}
}

RIS

TY  - JOUR
TI  - The Devil is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection
AU  - Hugues Moreau
AU  - Andrea Vassilev
AU  - Liming Chen
PY  - 2022
JO  - IEEE Transactions on Intelligent Transportation Systems
DO  - 10.1109/tits.2021.3110949
UR  - https://doi.org/10.1109/tits.2021.3110949
ER  -

APA

Moreau, H., Vassilev, A., & Chen, L. (2022). The Devil is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2021.3110949

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crossref · retrieved 2026-09-25T08:51:58.958Z