Human Face Age Recognition Based on Convolutional Neural Networks

DOI

10.2991/csece-18.2018.36How to use a DOI?

Keywords

human face age recognition; convolutional neural networks; CNN-AGE; caffe

Abstract

In the field of image recognition, the issue of face age recognition has attracted the attention of many scholars, and a lot of outstanding algorithms have been proposed, but the correctness rate of age recognition is not high. To improve the AGE identification accuracy, this paper proposes a face AGE recognition based on convolutional neural network (CNN) -- the AGE model, the IMDB - WIKI database and Caffe framework for training and testing, and the AGE recognition has the highest accuracy of 52%. Through experiments, this model is proved to be scientific and provides new ideas and methods for the study of face age recognition.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zijiang Zhu
AU  - Yi Hu
AU  - Dong Liu
AU  - Xiaoguang Deng
AU  - Junshan Li
PY  - 2018/02
DA  - 2018/02
TI  - Human Face Age Recognition Based on Convolutional Neural Networks
BT  - Proceedings of the 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)
PB  - Atlantis Press
SP  - 170
EP  - 173
SN  - 2352-538X
UR  - https://doi.org/10.2991/csece-18.2018.36
DO  - 10.2991/csece-18.2018.36
ID  - Zhu2018/02
ER  -