Open Access
| Issue |
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01065 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/e3sconf/202339101065 | |
| Published online | 05 June 2023 | |
- Wang, Huafeng, Yunhong Wang, and Yuan Cao. Video-based face recognition: A survey. International Journal of Computer and Information Engineering 3, no. 12 (2009) [Google Scholar]
- Ismail, Nurulhuda, Mas Idayu Md Sabri. Review of existing algorithms for face detection and recognition. In 8th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, pp. 30–39 (2009) [Google Scholar]
- R. Ranjan et al., A Fast and Accurate System for Face Detection, Identification, and Verification, in IEEE Transactions on Biometrics, Behaviour, and Identity Science, vol. 1, no. 2, pp. 82–96, April (2019) [CrossRef] [Google Scholar]
- W. Wu, Y. Yin, X. Wang and D. Xu, Face Detection with Different Scales Based on Faster R-CNN, in IEEE Transactions on Cybernetics, vol. 49, no. 11, pp. 4017–4028, Nov. (2019) [Google Scholar]
- Mool, Akshay, J. Panda, and Kapil Sharma. Optimizable face detection and tracking model with occlusion resolution for high quality videos. Multimedia Tools and Applications 81, no. 8 (2022) [Google Scholar]
- Kharchevnikova, Angelina, and Andrey V. Savchenko. Efficient video face recognition based on frame selection and quality assessment, PeerJ Computer Science 7 (2021) [Google Scholar]
- R. Abed, S. Bahroun and E. Zagrouba, Face Retrieval in Videos using Face Quality Assessment and Convolution Neural Networks, 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj- Napoca, Romania, (2020) [Google Scholar]
- J. Hernandez-Ortega, J. Fierrez, I. Serna and A. Morales, FaceQgen: Semi-Supervised DL for Face Image Quality Assessment, 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), Jodhpur, India, (2021) [Google Scholar]
- Ciaparrone, Gioele, Leonardo Chiariglione, and Roberto Tagliaferri. A comparison of DL models for end-to-end face-based video retrieval in unconstrained videos. Neural Computing and Applications 34, no. 10 (2022) [Google Scholar]
- Kharchevnikova, Angelina, and Andrey V. Savchenko. Efficient video face recognition based on frame selection and quality assessment. PeerJ Computer Science 7 (2021) [Google Scholar]
- Ou, Fu-Zhao, Xingyu Chen, Ruixin Zhang, Yuge Huang, Shaoxin, Li, Jilin, Li, Yong, Li, Liujuan Cao, and Yuan-Gen Wang. “SDD-FIQA: unsupervised face image quality assessment with similarity distribution distance. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7670–7679. (2021) [Google Scholar]
- Huang, Yu-Hsuan, and Homer H. Chen. Deep face recognition for dim images. Pattern Recognition 126 (2022) [Google Scholar]
- Ciaparrone, Gioele, Leonardo Chiariglione, and Roberto Tagliaferri. A comparison of DL models for end-to-end face-based video retrieval in unconstrained videos. Neural Computing and Applications 34, no. 10 (2022) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.