Cross-resolution face identification using deep-convolutional neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-021-10745-y.pdf
Reference58 articles.
1. Abate AF, Nappi M, Riccio D, Sabatino G (2007) 2D and 3D face recognition: a survey. Pattern Recogn Lett 28(14):1885–1906
2. Ahmed A, Guo J, Ali F, et al (2018) LBPH based improved face recognition at low resolution. In:International Conference on Artificial Intelligence and Big Data (ICAIBD) pp. 144-147. IEEE.
3. Alobaidi T, Mikhael W B (2018) A wavelet domain implementation of sparse representation method for face recognition. In 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS) pp. 214-217. IEEE
4. Anas IY, Bamgbose BO, Nuhu S (2019) A comparison between 2D and 3D methods of quantifying facial morphology. Heliyon 5(6):e01880
5. Arya K V, Rajawat A, Pandey M K, Rajput S S (2017) Very low resolution face recognition using fused visual and texture features. In: Conference on Information and Communication Technology (CICT) pp. 1-5. IEEE.
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