Classifying Image Sequences with the Markov Chain Structure and Matrix Normal Distributions

DOI10.1007/978-3-030-20912-4_54zbMath1529.62067MaRDI QIDQ6184700

Ewaryst Rafajłowicz

Publication date: 29 January 2024

Published in: Artificial Intelligence and Soft Computing (Search for Journal in Brave)

zbMATH Keywords

matrix normal distributionBayesian classifierclassification of image sequences

Mathematics Subject Classification ID

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

Cites Work

• Discriminant analysis of multivariate repeated measures data with Kronecker product structured covariance matrices
• The multilinear normal distribution: introduction and some basic properties
• Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion
• Detection of Essential Changes in Spatio-Temporal Processes with Applications to Camera Based Quality Control
• On Estimation of Covariance Matrices With Kronecker Product Structure
• Classifiers for doubly multivariate data
• Sequential detection of three-dimensional signals under dependent noise

This page was built for publication: Classifying Image Sequences with the Markov Chain Structure and Matrix Normal Distributions