Recent Advances in Statistical Mixture Models: Challenges and Applications

Sami Bourouis

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Paper

Recent Advances in Statistical Mixture Models: Challenges and Applications

Topics: Image and Video Analysis and Understanding; Machine Learning Methods

In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 312-319, 2023 , Lisbon, Portugal

Author: Sami Bourouis

Affiliation: Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

Keyword(s): Mixture Model, Finite And Infinite Models, Learning Techniques, Applications.

Abstract: This paper discusses current advances in mixture models, as well as modern approaches and tools that make use of mixture models. In particular, the contribution of mixture-based modeling in various area of researches is discussed. It exposes many challenging issues, especially the way of selecting the optimal model, estimating the parameters of each component, and so on. Some of newly emerging mixture model-based methods that can be applied successfully are also cited. Moreover, an overview of latest developments as well as open problems and potential research directions are discussed. This study aims to demonstrate that mixture models may be consistently proposed as a powerful tool for carrying out a variety of difficult real-life tasks. This survey can be the starting point for beginners as it allows them to better understand the current state of knowledge and assists them to develop and evaluate their own frameworks.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Bourouis, S. (2023). Recent Advances in Statistical Mixture Models: Challenges and Applications. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-626-2; ISSN 2184-4313, SciTePress, pages 312-319. DOI: 10.5220/0011660900003411

@conference{icpram23,
author={Sami Bourouis},
title={Recent Advances in Statistical Mixture Models: Challenges and Applications},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2023},
pages={312-319},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011660900003411},
isbn={978-989-758-626-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Recent Advances in Statistical Mixture Models: Challenges and Applications
SN - 978-989-758-626-2
IS - 2184-4313
AU - Bourouis, S.
PY - 2023
SP - 312
EP - 319
DO - 10.5220/0011660900003411
PB - SciTePress