LRTI: landmark ratios with task importance toward accurate age estimation using deep neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-06955-6.pdf
Reference44 articles.
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3. Niu Z, Zhou M, Wang L, Gao X, Hua G (2016) Ordinal regression with multiple output cnn for age estimation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, Las Vegas, NV, USA,pp. 4920–4928. https://doi.org/10.1109/CVPR.2016.532
4. Yang HF, Lin BY, Chang KY, Chen CS (2018) Joint estimation of age and expression by combining scattering and convolutional networks. ACM Trans Multimed Comput Commun Appl (TOMM)14(1): 1–18. https://doi.org/10.1145/3152118
5. Duan M, Li K, Li K (2017) An ensemble CNN2ELM for age estimation. IEEE Trans Inf Forensics Secur 13(3):758–772. https://doi.org/10.1109/TIFS.2017.2766583
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