Proceedings of the 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)

Human Face Age Recognition Based on Convolutional Neural Networks

Authors
Zijiang Zhu, Yi Hu, Dong Liu, Xiaoguang Deng, Junshan Li
Corresponding Author
Zijiang Zhu
Available Online February 2018.
DOI
https://doi.org/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.
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Proceedings
2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)
Part of series
Advances in Computer Science Research
Publication Date
February 2018
ISBN
978-94-6252-487-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/csece-18.2018.36How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/csece-18.2018.36
DO  - https://doi.org/10.2991/csece-18.2018.36
ID  - Zhu2018/02
ER  -