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JCR Impact Factor: 0.700
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Issues per year: 4
Current issue: Nov 2024
Next issue: Feb 2025
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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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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

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2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  2/2024 - 8

Development of a Very Low-Cost Deforestation Monitoring System Based on Aerial Image Clustering and Compression Techniques

ANDREI, A.-T. See more information about ANDREI, A.-T. on SCOPUS See more information about ANDREI, A.-T. on IEEExplore See more information about ANDREI, A.-T. on Web of Science, GRIGORE, O. See more information about GRIGORE, O. on SCOPUS See more information about GRIGORE, O. on SCOPUS See more information about GRIGORE, O. on Web of Science
 
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Download PDF pdficon (3,579 KB) | Citation | Downloads: 429 | Views: 490

Author keywords
computer vision, discrete cosine transforms, discrete Fourier transforms, discrete wavelet transforms, Gaussian mixture model

References keywords
clustering(6), sensing(5), remote(5), model(5), mixture(5), image(5), grigore(5), gaussian(5), segmentation(4), pattern(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2024-05-31
Volume 24, Issue 2, Year 2024, On page(s): 73 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.02008
Web of Science Accession Number: 001242091800008
SCOPUS ID: 85195651048

Abstract
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Clustering holds significant utility across a spectrum of several domains, including pattern recognition, image analysis, customer analytics, market segmentation, social network analysis, and numerous other areas. The main advantages of image clustering are its degree of freedom regarding data labeling and the lack of training and model deployment, which makes them suitable for the overall studys purpose of land cover segmentation and deforestation monitoring. In previous work, the Gaussian Mixture Model (GMM) technique has been established as the best option. Due to the necessity of implementing the algorithm on light unmanned airborne platforms for fast deforestation monitoring, the high resources and long computation time became an issue. This paper proposes several cost-efficient GMM clustering algorithms based on discrete transforms traditionally used for image compression. The results will show that the proposed methods maintain the clustering output quality while drastically decreasing the computation time and also lowering the memory needed to perform.


References | Cited By  «-- Click to see who has cited this paper

[1] K. Pearson, "Contributions to the mathematical theory of evolution," University College, London, vol. 185, pp. 71-110, 1894.
[CrossRef]


[2] A. P. Dempster, N. M. Laird, D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," Royal Statistical Society, vol. 39, no. 1, pp. 1-22, 1977.
[CrossRef] [Web of Science Times Cited 33430]


[3] Y. Tarabalka, J. A. Benediktsson, J. Chanussot, "Spectral-spatial classification of hyperspectral imagery based on partitional clustering techniques," IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 8, pp. 2973-2987, 2009.
[CrossRef] [Web of Science Times Cited 566] [SCOPUS Times Cited 661]


[4] H. Permuter, J. Francos, I. Jermyn, "A study of Gaussian mixture models of color and texture features for image classification and segmentation," Pattern Recognition, Elsevier, vol. 39, no. 4, pp. 695-706, 2006.
[CrossRef] [Web of Science Times Cited 250] [SCOPUS Times Cited 329]


[5] X.-H. Wu, R. Hu, Y.-Q. Bao, "Coarse-to-fine method for vision-based pedestrian traffic light detection," Advances in Electrical and Computer Engineering, vol. 20, no. 1, pp. 43-48, 2020.
[CrossRef] [Full Text] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[6] A.-T., Andrei, O. Grigore, "Unsupervised machine learning algorithms used in deforested areas monitoring," International Conference on E-Health and Bioengineering, Iasi, Romania, pp. 1-4, 2021.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 7]


[7] A.-T., Andrei, O. Grigore, "Combating deforestation using different AGNES approaches," 14th International Conference on Communications (COMM), Bucharest, Romania, pp. 1-5, 2022.
[CrossRef] [SCOPUS Times Cited 4]


[8] A.-T., Andrei, O. Grigore, "Mean shift clustering with bandwidth estimation and color extraction module used in forest segmentation," 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, Romania, pp. 1-6, 2023.
[CrossRef] [SCOPUS Times Cited 2]


[9] A.-T., Andrei, O. Grigore, "Gaussian mixture model application in deforestation monitoring," International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Ankara, Turkey, pp. 26-31, 2022.
[CrossRef] [SCOPUS Times Cited 4]


[10] W. Emery, A. Camps, "Chapter 3 - Optical imaging systems, introduction to satellite remote sensing," Introduction to Satellite Remote Sensing, Elsevier, pp. 85-130, 2017.
[CrossRef] [Web of Science Times Cited 4]


[11] H. Al-Jubouri, H. Du, H. Sellahewa, "Applying Gaussian mixture model on discrete cosine features for image segmentation and classification," 4th Computer Science and Electronic Engineering Conference (CEEC), Colchester, UK, pp. 194-199, 2012.
[CrossRef] [SCOPUS Times Cited 7]


[12] L. Jiao, T. Denoeux, Z. Liu, Q. Pan, "EGMM: An evidential version of the Gaussian mixture model for clustering," Applied Soft Computing, vol. 129, no. C, 2022.
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 28]


[13] N. X. Vinh, J. Epps, J. Bailey, "Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance," The Journal of Machine Learning Research, vol. 11, pp. 2837-2854, 2010.

[14] W. M. Rand, "Objective criteria for the evaluation of clustering methods," Journal of the American Statistical Association, pp. 846-850, 2012.
[CrossRef] [SCOPUS Times Cited 4807]


[15] G. Exarchakis, O. Oubari, G. Lenz, "A sampling-based approach for efficient clustering in large datasets," 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12393-12402, 2022.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 4]


[16] K. R. Rao, P. Yip, "Discrete cosine transform," Algorithms, Advantage Applications, Academic Press, 1990.
[CrossRef]


[17] R. Gonzalez, R. Woods, "Digital image processing," Addison-Wesley Publishing Company, pp. 81-125, 1992

[18] C. K. Chui, "An introduction to wavelets," Mathematics of Computation, JSTOR, vol. 60, no. 202, pp. 854, 1993.
[CrossRef]


[19] D. A. Reynolds, "Gaussian mixture models," Encyclopedia of biometrics, Springer, Boston, MA, pp. 659-663, 2009.
[CrossRef]


[20] S. K. Ng, T. Krishnan, G. J. McLachlan, "The EM algorithm," Handbook of Computational Statistics, Springer, Berlin, Heidelberg, pp. 139-172, 2012.
[CrossRef]


[21] T. O. Hodson, "Root-mean-square error (RMSE) or mean absolute error (MAE): When to use them or not," Geoscientific Model Development, vol. 15, no. 14, pp. 5481-5487, 2022.
[CrossRef] [Web of Science Times Cited 383] [SCOPUS Times Cited 467]


[22] D. L. Davies, D. W. Bouldin, "A cluster separation measure," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-1, no. 2, pp. 224-227, 1979.
[CrossRef]


[23] G. Hudson, A. Leger, B. Niss, I. Sebestyen, J. Vaaben, "JPEG-1 standard 25 years: Past, present, and future reasons for a success," Journal of Electronic Imaging, vol. 27, no. 4, 2018.
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 55]


[24] T. Giannakopoulos, A. Pikrakis, "Signal transforms and filtering essentials," Academic Press, pp. 33-57, 2014.
[CrossRef]


[25] W. B. Pennebaker, L. J. Mitchell, "JPEG: Still image data compression standard," Van Nostrand Reinhold, 1993

[26] C. M. Bishop, "Pattern recognition and machine learning," Springer Science, pp. 424-430, 2006.
[CrossRef]


[27] F. Cao, L. Liu, L. Li, "Short-wave infrared photodetector," Materials Today, vol. 62, pp. 327-349, 2023.
[CrossRef] [Web of Science Times Cited 69] [SCOPUS Times Cited 74]


[28] T. Zhang, T. Zeng, X. Zhang, "Synthetic aperture radar (SAR) meets deep learning," Remote Sensing, vol. 15, no. 2, pp. 303, 2023.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 16]


[29] T. N. Tu, H. N. Hoang, D. D. Van, T. V. Van, A. D. Duy, "An improvement of kmeans algorithm using wavelet technique to increase speed of clustering remote sensing images", International Journal of Computer and Electrical Engineering, vol. 8, no. 2, pp.177-184, 2016.
[CrossRef]


[30] X. Zou, X. Xu, C. Qing, X. Xing, "High speed deep networks based on Discrete Cosine Transformation," 2014 IEEE International Conference on Image Processing (ICIP), Paris, France, pp. 5921-5925, 2014.
[CrossRef] [SCOPUS Times Cited 21]


[31] A.-T., Andrei, O. Grigore, "Low-cost optimized u-net model with gmm automatic labeling used in forest semantic segmentation", Sensors, vol. 23, no. 21, pp. 8991, 2023.
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]




References Weight

Web of Science® Citations for all references: 34,792 TCR
SCOPUS® Citations for all references: 6,488 TCR

Web of Science® Average Citations per reference: 1,087 ACR
SCOPUS® Average Citations per reference: 203 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-04 08:01 in 200 seconds.




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