Masked contrastive graph representation learning for age estimation-Reference-Cited by-同舟云学术

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Masked contrastive graph representation learning for age estimation

Published:2025-02 Issue: Volume:158 Page:110974
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Shou Yuntao,Cao Xiangyong,Liu Huan,Meng Deyu

Funder

Key Laboratory of Engineering Plastics, Chinese Academy of Sciences

China Knowledge Centre for Engineering Sciences and Technology

National Natural Science Foundation of China

Natural Science Foundation of Shaanxi Province

Publisher

Elsevier BV

Reference45 articles.

1. Hierarchical attention-based age estimation and bias analysis;Hiba;IEEE Trans. Pattern Anal. Mach. Intell.,2023

2. G. Levi, T. Hassner, Age and gender classification using convolutional neural networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015, pp. 34–42.

3. Improving face-based age estimation with attention-based dynamic patch fusion;Wang;IEEE Trans. Image Process.,2022

4. Vision gnn: An image is worth graph of nodes;Han;Adv. Neural Inf. Process. Syst.,2022

5. TAA-gcn: A temporally aware adaptive graph convolutional network for age estimation;Korban;Pattern Recognit.,2023

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