Utilizing CNNs and transfer learning of pre-trained models for age range classification from unconstrained face images
作者：
Highlights：
• Extensive utilization of several pre-trained networks to evaluate the best architecture for age range classification.
• A dimensionality reduction method is presented in order to enhance the extracted features.
• Robust features are generated by utilizing several features from distinct domain-based tasks.
• Age range estimation from unconstrained face images is studied.
摘要
•Extensive utilization of several pre-trained networks to evaluate the best architecture for age range classification.•A dimensionality reduction method is presented in order to enhance the extracted features.•Robust features are generated by utilizing several features from distinct domain-based tasks.•Age range estimation from unconstrained face images is studied.
论文关键词：Age range classification,CNNs,Deep learning,Deep neural networks (DNNs),Face recognition
论文评审过程：Received 16 March 2017, Revised 3 February 2019, Accepted 2 May 2019, Available online 9 May 2019, Version of Record 23 May 2019.
论文官网地址：https://doi.org/10.1016/j.imavis.2019.05.001
