Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios

Chen Wang, Fen Liu

Open source

DOI: 10.1109/access.2025.3581428
Published: 2025
Container: IEEE Access
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1109/access.2025.3581428,
  title = {Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios},
  author = {Chen Wang and Fen Liu},
  year = {2025},
  journal = {IEEE Access},
  doi = {10.1109/access.2025.3581428},
  url = {https://doi.org/10.1109/access.2025.3581428}
}

RIS

TY  - JOUR
TI  - Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios
AU  - Chen Wang
AU  - Fen Liu
PY  - 2025
JO  - IEEE Access
DO  - 10.1109/access.2025.3581428
UR  - https://doi.org/10.1109/access.2025.3581428
ER  -

APA

Wang, C., & Liu, F. (2025). Ghost Module-Enhanced MTCNN: A Lightweight Cascade Framework for High-Accuracy Face Detection in Edge-Deployable Scenarios. IEEE Access. https://doi.org/10.1109/access.2025.3581428

Source records

crossref · retrieved 2026-11-10T09:31:03.212Z