Apparent Age Estimation with CNN
- 10.2991/icmmita-16.2016.30How to use a DOI?
- age estimation; convolutional neural networks ;IMDB-WIKI dataset .
Apparent age estimation from face image has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. In this paper ,we tackle the estimation of apparent age in still face images with deep convolutional neural networks (CNN).Our convolutional neural network use the GoogLeNet architecture, add batch normalization layer after each ReLU operation and remove all the dropout operations to accelerate the convergence of this very large-scale deep network. In addition, due to the limited number of apparent age annotated images, we train the deep models with several datasets in a cascaded way. Firstly, We pre-train a real age estimation model using IMDB-WIKI dataset, and then ne-tune the deep model with combined dataset with multiple real-age labeled databases .Finally, the apparent age data from the challenge are used to ne-tune the deep model parameters for apparent age estimation.
- © 2017, 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/).
Cite this article
TY - CONF AU - Zhiqin Zhang PY - 2017/01 DA - 2017/01 TI - Apparent Age Estimation with CNN BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 152 EP - 157 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-16.2016.30 DO - 10.2991/icmmita-16.2016.30 ID - Zhang2017/01 ER -