Gabor filter bank with deep autoencoder based face recognition system
作者：
Highlights：
• We propose an efficient face recognition system based on Gabor filter bank and SAE.
• Gabor filters have not been adequately coupled with deep learning schemes.
• Sparse Auto-Encoder ameliorates the features generated by Gabor filters.
• The proposed system outperforms existing methods on seven popular face databases.
• The proposed system can achieve optimal results.
摘要
•We propose an efficient face recognition system based on Gabor filter bank and SAE.•Gabor filters have not been adequately coupled with deep learning schemes.•Sparse Auto-Encoder ameliorates the features generated by Gabor filters.•The proposed system outperforms existing methods on seven popular face databases.•The proposed system can achieve optimal results.
论文关键词：Sparse AutoEncoder,Gabor filter bank,Face recognition,PCA+LDA
论文评审过程：Received 3 October 2020, Revised 9 January 2022, Accepted 22 February 2022, Available online 26 February 2022, Version of Record 2 March 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116743
