Beyond global fusion: a group-aware fusion approach for multi-view image clustering

DOI10.1016/j.ins.2019.04.034zbMath1451.68236OpenAlexW2940686350WikidataQ128009992 ScholiaQ128009992MaRDI QIDQ2215012

Qingming Huang, Shuhui Wang, Guorong Li, Zhe Xue, Jun Huang, Weigang Zhang

Publication date: 10 December 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2019.04.034

zbMATH Keywords

multi-view learningimage clusteringgroup-aware fusionlocal fusion strategy

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)

Related Items (1)

Multi-view fuzzy clustering of deep random walk and sparse low-rank embedding

Uses Software

• SIFT

Cites Work

• Multi-view clustering based on graph-regularized nonnegative matrix factorization for object recognition
• Multiple kernel clustering based on centered kernel alignment
• Low-rank representation with adaptive graph regularization
• Joint multi-view representation and image annotation via optimal predictive subspace learning
• Unsupervised Feature Selection via Nonnegative Spectral Analysis and Redundancy Control
• Weakly Supervised Deep Matrix Factorization for Social Image Understanding
• 10.1162/153244303321897735
• Group-Sensitive Multiple Kernel Learning for Object Recognition
• Modeling the shape of the scene: A holistic representation of the spatial envelope

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