International Journal of Applied Sciences and Smart Technologies
Volume 01, Issue 01, June 2019

Development Study of Deep Learning Facial Age Estimation

Puspaningtyas Sanjoyo Adi (Universitas Sanata Dharma)

Article Info

Publish Date
21 Jun 2019

Abstract

Human age estimation is one of the most challenging problem because it can be used in many applications relating to age such as age-specific movies, age-specific computer applications or website, etc. This paper will contribute to give brief information about development of age estimation researches using deep learning. We explore three recent journal papers that give significant contribution in age estimation using deep learning. From these papers, they selected classification methods and there is gradual improvement in result and also in selected loss function. The best result gives MAE (mean average error) 2.8 years and VGG-16 is the most selected CNN architecture.

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Journal Info
International Journal of Applied Sciences and Smart Technologies
Website

Abbrev

IJASST

Publisher

Universitas Sanata Dharma

Subject

Computer Science & IT Energy Engineering Industrial & Manufacturing Engineering

Description

International Journal of Applied Sciences and Smart Technologies (IJASST) is published by Faculty of Science and Technology, Sanata Dharma University Yogyakarta-Central Java-Indonesia. IJASST is an open-access peer reviewed journal that mediates the dissemination of academicians, researchers, and ...