Multivariate‐bounded Gaussian mixture model with minimum message length criterion for model selection-Reference-Cited by-同舟云学术

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Multivariate‐bounded Gaussian mixture model with minimum message length criterion for model selection

Published:2021-03-16 Issue:5 Volume:38 Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Azam Muhammad¹^ORCID,Bouguila Nizar²^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering Concordia University Montreal Canada

2. Concordia Institute for Information Systems Engineering Concordia University Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12688

Reference97 articles.

1. Agusta Y. &Dowe D. L.(2003).Unsupervised learning of correlated multivariate gaussian mixture models using mml. Australasian Joint Conference on Artificial Intelligence. pp. 477–489.

2. A new look at the statistical model identification

3. Wavelet Modeling Using Finite Mixtures of Generalized Gaussian Distributions: Application to Texture Discrimination and Retrieval

4. Texture Modeling Using Contourlets and Finite Mixtures of Generalized Gaussian Distributions and Applications

5. Finite general Gaussian mixture modeling and application to image and video foreground segmentation

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