Multi-view low-rank sparse subspace clustering

Maria Brbić; Ivica Kopriva

doi:10.1016/j.patcog.2017.08.024

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-view low-rank sparse subspace clustering

Maria Brbić Ivica Kopriva

Year: 2017 Journal: Pattern Recognition Vol: 73 Pages: 247-258 Publisher: Elsevier BV

DOI: 10.1016/j.patcog.2017.08.024

Get Full-Text PDF Get Analytical Report

Keywords:

Cluster analysis Linear subspace Spectral clustering Subspace topology Rank (graph theory) Computer science Kernel (algebra) Representation (politics) Algorithm Matrix (chemical analysis) Mathematics Pattern recognition (psychology) Artificial intelligence Combinatorics

Metrics

455

Cited By

30.05

FWCI (Field Weighted Citation Impact)

Refs

1.00

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Multi-view low-rank sparse subspace clustering

Metrics

Citation History

Topics

Related Documents

Latent Low-Rank Sparse Multi-view Subspace Clustering

Low-Rank Multi-View Subspace Clustering Based on Sparse Regularization

Low-Rank And Sparse Tensor Representation For Multi-View Subspace Clustering

Facilitated low-rank multi-view subspace clustering

Nonconvex low-rank and sparse tensor representation for multi-view subspace clustering