Face Recognition

We developed a Face Recognition system that only require CPUs for training on a small-size training dataset, but can compete with SOTA in term of accuracy and speed. Moreover, the system has online learning ability. We published 2 papers with the system.

Please find more details of our algorithm with our 2 publications below:

(Nguyen et al., 2023) and (Dat et al., 2021)

References

2023

Hybrid end-to-end approach integrating online learning with face-identification system

Dat Nguyen , Trung Son Nguyen , Hong Anh Thi Pham , and 2 more authors

Computer Science, 2023

Bib PDF

@article{van2023hybrid,
  title = {Hybrid end-to-end approach integrating online learning with face-identification system},
  author = {Nguyen, Dat and Nguyen, Trung Son and Pham, Hong Anh Thi and Hoang, Thao Thu and Thanh, Ta Minh},
  journal = {Computer Science},
  volume = {24},
  number = {2},
  year = {2023},
}

2021

A novel approach to end-to-end facial recognition framework with virtual search engine elasticsearch

Nguyen Dat , Son Nguyen Trung , Anh Pham Thi Hong , and 2 more authors

In Computational Science and Its Applications–ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part III 21 , 2021

Bib PDF

@inproceedings{van2021novel,
  title = {A novel approach to end-to-end facial recognition framework with virtual search engine elasticsearch},
  author = {Dat, Nguyen and Trung, Son Nguyen and Hong, Anh Pham Thi and Hoang, Thao Thu and Thanh, Ta Minh},
  booktitle = {Computational Science and Its Applications--ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13--16, 2021, Proceedings, Part III 21},
  pages = {454--470},
  year = {2021},
  organization = {Springer},
}