Face Recognition Research and Development
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43567-6_1
Reference282 articles.
1. Aggarwal, D., Zhou, J., Jain, A.K.: Fedface: collaborative learning of face recognition model. In: IJCB, pp. 1–8 (2021)
2. Aghdam, O.A., Bozorgtabar, B., Ekenel, H.K., Thiran, J.P.: Exploring factors for improving low resolution face recognition. In: CVPRW, pp. 2363–2370 (2019)
3. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE TPAMI 28(12), 2037–2041 (2006)
4. Al Jazaery, M., Guo, G.: Automated cleaning of identity label noise in a large face dataset with quality control. IET Biometrics 9(1) (2020)
5. Albiero, V., Zhang, K., Bowyer, K.W.: How does gender balance in training data affect face recognition accuracy? In: IJCB, pp. 1–10 (2020)
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