Human Face Age Recognition Based on Convolutional Neural Networks
Zijiang Zhu, Yi Hu, Dong Liu, Xiaoguang Deng, Junshan Li
Available Online February 2018.
- https://doi.org/10.2991/csece-18.2018.36How to use a DOI?
- human face age recognition; convolutional neural networks; CNN-AGE; caffe
- 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.
- 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 -