Predictive high-level feature representation based on dictionary learning
作者：
Highlights：
• New constraint to enforce label consistency of sparse coding is proposed.
• An efficient linear model of sparse coding prediction with low cost is introduced.
• This method provides promising classification accuracy compared with others.
• The proposed method clearly outperforms in terms of computation time.
• This method can be considered to apply in real-time classification problems.
摘要
•New constraint to enforce label consistency of sparse coding is proposed.•An efficient linear model of sparse coding prediction with low cost is introduced.•This method provides promising classification accuracy compared with others.•The proposed method clearly outperforms in terms of computation time.•This method can be considered to apply in real-time classification problems.
论文关键词：Dictionary learning,High-level feature representation,K-SVD,Sparse coding,Supervised learning
论文评审过程：Received 29 March 2016, Revised 10 October 2016, Accepted 10 October 2016, Available online 14 October 2016, Version of Record 26 October 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.019
