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A review on suppressed fuzzy c-means clustering models Cover

A review on suppressed fuzzy c-means clustering models

Acta Universitatis Sapientiae, Informatica
Volume 12 (2020): Issue 2 (December 2020)
By: László Szilágyi,  László Lefkovits and  David Iclanzan  
Open Access
|Jan 2021

Authors

László Szilágyi

lalo@ms.sapientia.ro

Sapientia Hungarian University of Transylvania, Dept. of Electrical Engineering, Târgu Mureş, Óbuda University, University Research, Innovation and Service Center, Cluj-Napoca

László Lefkovits

lefkolaci@ms.sapientia.ro

Sapientia Hungarian University of Transylvania, Dept. of Electrical Engineering, Cluj-Napoca, Romania

David Iclanzan

iclanzan@ms.sapientia.ro

Sapientia Hungarian University of Transylvania, Dept. of Mathematics-Informatics, Cluj-Napoca, Romania
DOI: https://doi.org/10.2478/ausi-2020-0018 | Journal eISSN: 2066-7760
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Language: English
Page range: 302 - 324
Submitted on: Nov 15, 2020
|
Accepted on: Nov 21, 2020
|
Published on: Jan 29, 2021
Published by: Sapientia Hungarian University of Transylvania
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
fuzzy c-means algorithm,
suppressed fuzzy c-means algorithm,
image segmentation,
data mining
Related subjects:
Computer sciences,
Computer sciences, other

© 2021 László Szilágyi, László Lefkovits, David Iclanzan, published by Sapientia Hungarian University of Transylvania
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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