A BFS-Tree of ranking references for unsupervised manifold learning

作者：

Highlights：

• A novel unsupervised manifold learning algorithm based on the BFS- Tree of Ranking References.

• The structure of the tree is exploited to discovery underlying similarity relationships.

• Based on the discovered relationships, a more effective similarity measure is computed.

• Several experiments considering various datasets, features and comparison with state-of-the-art methods.

摘要

•A novel unsupervised manifold learning algorithm based on the BFS- Tree of Ranking References.•The structure of the tree is exploited to discovery underlying similarity relationships.•Based on the discovered relationships, a more effective similarity measure is computed.•Several experiments considering various datasets, features and comparison with state-of-the-art methods.

论文关键词：Content-based image retrieval,Unsupervised manifold learning,Tree representation,Ranking references

论文评审过程：Received 22 July 2018, Revised 16 January 2020, Accepted 18 September 2020, Available online 24 September 2020, Version of Record 5 October 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107666