An effective region force for some variational models for learning and clustering

DOI10.1007/s10915-017-0429-4zbMath1419.62159OpenAlexW2605215001MaRDI QIDQ1703055

Ke Yin, Xue-Cheng Tai

Publication date: 1 March 2018

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-017-0429-4

zbMATH Keywords

graphical modelmulti-class segmentationsemi-supervised clusteringChan-Vese modelregion force penalty

Mathematics Subject Classification ID

Multivariate analysis (62H99) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (7)

Convex object(s) characterization and segmentation using level set function ⋮ Proximal gradient methods for general smooth graph total variation model in unsupervised learning ⋮ A compressed sensing based least squares approach to semi-supervised local cluster extraction ⋮ Nonlocal regularized CNN for image segmentation ⋮ Variational community partition with novel network structure centrality prior ⋮ A multigrid algorithm for maxflow and min-cut problems with applications to multiphase image segmentation ⋮ Compressive Sensing for Cut Improvement and Local Clustering

Uses Software

• Vlfeat

Cites Work

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