Supervised dictionary learning with multiple classifier integration

作者：

Highlights：

• Multiple classifier learning is integrated into sparse dictionary learning.

• The proposed algorithm simultaneously updates dictionary and classifiers.

• The proposed method can largely improve the discriminability of sparse codes.

• An interesting insight into label consistency from the view of ensemble learning.

• The experiments show the excellent performance of the proposed method.

摘要

Highlights•Multiple classifier learning is integrated into sparse dictionary learning.•The proposed algorithm simultaneously updates dictionary and classifiers.•The proposed method can largely improve the discriminability of sparse codes.•An interesting insight into label consistency from the view of ensemble learning.•The experiments show the excellent performance of the proposed method.

论文关键词：Sparse coding,Supervised dictionary learning,Multiple classifier learning,Image classification

论文评审过程：Received 28 March 2015, Revised 11 December 2015, Accepted 25 January 2016, Available online 23 February 2016, Version of Record 21 March 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.01.028