Enhancing Low-Rank Subspace Clustering by Manifold Regularization

DOI10.1109/TIP.2014.2343458zbMath1374.68472DBLPjournals/tip/LiuCZX14WikidataQ46080016 ScholiaQ46080016MaRDI QIDQ4592445

Junmin Liu, Jiang-She Zhang, Yijun Chen, Zong Ben Xu

Publication date: 20 November 2017

Published in: IEEE Transactions on Image Processing (Search for Journal in Brave)

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Pattern recognition, speech recognition (68T10)

Related Items (6)

Nonnegative self-representation with a fixed rank constraint for subspace clustering ⋮ LGSLRR: towards fusing discriminative ordinal local and global structured low-rank representation for image recognition ⋮ Beyond linear subspace clustering: a comparative study of nonlinear manifold clustering algorithms ⋮ Low-rank representation with adaptive graph regularization ⋮ Sparse fuzzy two-dimensional discriminant local preserving projection (SF2DDLPP) for robust image feature extraction ⋮ Deep low-rank subspace ensemble for multi-view clustering

This page was built for publication: Enhancing Low-Rank Subspace Clustering by Manifold Regularization