Deep self-representative subspace clustering network
作者：
Highlights：
• Deep subspace clustering using self-representative network is proposed.
• Feature extraction and emphasis network using attention model is introduced.
• Dimensional reduction in self-expressive layer is presented.
• We experimentally verify performance improvements for the proposed approach.
摘要
•Deep subspace clustering using self-representative network is proposed.•Feature extraction and emphasis network using attention model is introduced.•Dimensional reduction in self-expressive layer is presented.•We experimentally verify performance improvements for the proposed approach.
论文关键词：Subspace clustering,Self-representation,Deep subspace clustering
论文评审过程：Received 10 September 2020, Revised 15 April 2021, Accepted 11 May 2021, Available online 19 May 2021, Version of Record 28 May 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.108041
