Stomped-\(t\): a novel probability distribution for rough-probabilistic clustering

DOI10.1016/J.INS.2017.08.083zbMath1436.68343OpenAlexW2751650611MaRDI QIDQ780979

Abhirup Banerjee, Pradipta Maji

Publication date: 16 July 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2017.08.083

zbMATH Keywords

image segmentationexpectation-maximization algorithmhidden Markov random field modelrough-probabilistic clusteringstomped normal distribution

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) Reasoning under uncertainty in the context of artificial intelligence (68T37) Distribution theory (60E99)

Related Items (1)

Fair clustering with fair correspondence distribution

Uses Software

• Unnamed Item
• FSL
• BET

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Interval set clustering of web users with rough \(K\)-means
• Image segmentation using a local GMM in a variational framework
• Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images
• A curious likelihood identity for the multivariate t-distribution
• Fuzzy C-Means Clustering With Local Information and Kernel Metric for Image Segmentation
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

This page was built for publication: Stomped-\(t\): a novel probability distribution for rough-probabilistic clustering