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JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Feb 2021
Next issue: May 2021
Avg review time: 56 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
Starting on the 15th of June 2020 we wiil introduce a new policy for reviewers. Reviewers who provide timely and substantial comments will receive a discount voucher entitling them to an APC reduction. Vouchers (worth of 25 EUR or 50 EUR, depending on the review quality) will be assigned to reviewers after the final decision of the reviewed paper is given. Vouchers issued to specific individuals are not transferable.

2019-Dec-16
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2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

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  3/2011 - 13

Application of Rosette Pattern for Clustering and Determining the Number of Cluster

SADR, A. See more information about SADR, A. on SCOPUS See more information about SADR, A. on IEEExplore See more information about SADR, A. on Web of Science, MOMTAZ, A. K. See more information about MOMTAZ, A. K. on SCOPUS See more information about MOMTAZ, A. K. on SCOPUS See more information about MOMTAZ, A. K. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (2,657 KB) | Citation | Downloads: 962 | Views: 3,429

Author keywords
clustering, Fuzzy C-means (FCM), pattern recognition, Rosette Pattern, validity index

References keywords
clustering(17), pattern(12), fuzzy(11), algorithms(8), recognition(7), data(7), analysis(7), rosette(5), hall(5), clusters(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 77 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03013
Web of Science Accession Number: 000296186700013
SCOPUS ID: 80055116504

Abstract
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Clustering is one of the most important research topics which has many practical applications such as medical imaging and Non-Destructive Testing (NDT). Most clustering algorithms like K-means, fuzzy C-Means (FCM) and their derivatives require the number of clusters as one of the initializing parameters. This paper proposes an algorithm for image clustering with no need to any initializing parameter. In this state-of-the-art, an image is sampled based on a rosette pattern and according to the pattern characteristics, the extracted samples are clustered and then the number of clusters is determined. The centroids of classes are computed by means of a method based on calculation of distribution function. Based on different data sets, the results show that the algorithm improves the capability of the clustering by a minimum of 62.26% and 87.62% in comparison with FCM and K-means algorithms, respectively. Moreover, in dealing with high resolution data sets, the efficiency of the algorithm in clusters detection and run time improvement increases considerably.


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Cited-By CrossRef

[1] Consistency Analysis of Ultrasound Echoes within a Dual Symmetric Path Inspection Framework, VASILE, C., STAMATESCU, G., SGARCIU, V., IOANA, C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 15, 2015.
Digital Object Identifier: 10.4316/AECE.2015.02006
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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