A Survey on Neural Networks for Face Age Estimation (CROSBI ID 713120)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Grd, Petra
engleski
A Survey on Neural Networks for Face Age Estimation
Age estimation is an important task and challenge in computer vision. It can be defined as determining real or apparent age or age group of a person in an image. Through recent years, a large number of age estimation algorithms have been developed and multiple approaches to age estimation have been presented. Nowadays neural networks, especially Convolutional Neural Networks (CNN) have become a standard for age estimation. This paper gives an overview of recent advances in age estimation with focus on neural networks and identifies future research directions. It answers the research questions such as: (RQ1) Which models for age estimation have been used? (RQ2) Which are the most commonly used datasets for testing age estimation algorithms using neural networks? (RQ3) Which performance measures and evaluation protocols are prevalent in age estimation algorithms testing? (RQ4) What is the current state of the art performance for age estimation algorithms using neural networks?
artificial neural networks ; convolutional neural networks ; age estimation ; age classification ; face ageing
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Podaci o prilogu
219-227.
2021.
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objavljeno
Podaci o matičnoj publikaciji
Vrček, Neven ; Pergler, Elisabeth ; Grd, Petra
Varaždin: Fakultet organizacije i informatike Sveučilišta u Zagrebu
1847-2001
1848-2295
Podaci o skupu
32nd Central European Conference on Information and Intelligent Systems (CECIIS 2021)
predavanje
13.10.2021-15.10.2021
Varaždin, Hrvatska