Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts

DOI10.1007/978-3-319-18461-6_19zbMath1444.62085OpenAlexW383032609MaRDI QIDQ3300302

Jörg Hendrik Kappes, Paul Swoboda, Bogdan Savchynskyy, Christoph Schnörr, Tamir Hazan

Publication date: 28 July 2020

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-18461-6_19

zbMATH Keywords

correlation clusteringmulticutperturb and MAP

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Image analysis in multivariate analysis (62H35)

Uses Software

• OpenGM

Cites Work

• Ambrosio-Tortorelli segmentation of stochastic images: model extensions, theoretical investigations and numerical methods
• Correlation clustering
• Nonparametric Bayesian image segmentation
• The partition problem
• Combinatorial theory.
• Continuous Multiclass Labeling Approaches and Algorithms
• Approximation of functional depending on jumps by elliptic functional via t-convergence
• A Survey of Statistical Network Models
• Graphical Models, Exponential Families, and Variational Inference
• On clusterings
• A Convex Approach to Minimal Partitions
• Unnamed Item
• Unnamed Item

This page was built for publication: Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts