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JCR Impact Factor: 0.800
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Current issue: Feb 2024
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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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2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

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.

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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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  2/2017 - 12

 HIGHLY CITED PAPER 

Cogent Confabulation based Expert System for Segmentation and Classification of Natural Landscape Images

BRAOVIC, M. See more information about BRAOVIC, M. on SCOPUS See more information about BRAOVIC, M. on IEEExplore See more information about BRAOVIC, M. on Web of Science, STIPANICEV, D. See more information about  STIPANICEV, D. on SCOPUS See more information about  STIPANICEV, D. on SCOPUS See more information about STIPANICEV, D. on Web of Science, KRSTINIC, D. See more information about KRSTINIC, D. on SCOPUS See more information about KRSTINIC, D. on SCOPUS See more information about KRSTINIC, D. on Web of Science
 
View the paper record and citations in View the paper record and citations in Google Scholar
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Download PDF pdficon (6,154 KB) | Citation | Downloads: 843 | Views: 2,868

Author keywords
expert systems, image classification, image color analysis, image segmentation, knowledge engineering

References keywords
image(12), processing(9), vision(7), detection(7), stipanicev(6), classification(6), smoke(5), segmentation(5), jakovcevic(5), fire(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 85 - 94
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02012
Web of Science Accession Number: 000405378100012
SCOPUS ID: 85020089483

Abstract
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Ever since there has been an increase in the number of automatic wildfire monitoring and surveillance systems in the last few years, natural landscape images have been of great importance. In this paper we propose an expert system for fast segmentation and classification of regions on natural landscape images that is suitable for real-time applications. We focus primarily on Mediterranean landscape images since the Mediterranean area and areas with similar climate are the ones most associated with high wildfire risk. The proposed expert system is based on cogent confabulation theory and knowledge bases that contain information about local and global features, optimal color spaces suitable for classification of certain regions, and context of each class. The obtained results indicate that the proposed expert system significantly outperforms well-known classifiers that it was compared against in both accuracy and speed, and that it is effective and efficient for real-time applications. Additionally, we present a FESB MLID dataset on which we conducted our research and that we made publicly available.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 6 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 8
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Updated 5 days, 21 hours ago

Cited-By CrossRef

[1] Comments on “MLCM: Multi-Label Confusion Matrix”, Krstinić, Damir, Šerić, Ljiljana, Slapničar, Ivan, IEEE Access, ISSN 2169-3536, Issue , 2023.
Digital Object Identifier: 10.1109/ACCESS.2023.3267672
[CrossRef]

[2] Burned area semantic segmentation: A novel dataset and evaluation using convolutional networks, Ribeiro, Tiago F.R., Silva, Fernando, Moreira, José, Costa, Rogério Luís de C., ISPRS Journal of Photogrammetry and Remote Sensing, ISSN 0924-2716, Issue , 2023.
Digital Object Identifier: 10.1016/j.isprsjprs.2023.07.002
[CrossRef]

[3] A Video Based Fire Smoke Detection Using Robust AdaBoost, Wu, Xuehui, Lu, Xiaobo, Leung, Henry, Sensors, ISSN 1424-8220, Issue 11, Volume 18, 2018.
Digital Object Identifier: 10.3390/s18113780
[CrossRef]

[4] Online Recognition Method for Target Maneuver in UAV Autonomous Air Combat, Li, Yicong, Yang, Zhen, Lv, Xiaofeng, Huang, Jichuan, Zhao, Yiyang, Zhou, Deyun, 2022 22nd International Conference on Control, Automation and Systems (ICCAS), ISBN 978-89-93215-24-3, 2022.
Digital Object Identifier: 10.23919/ICCAS55662.2022.10003924
[CrossRef]

[5] Application of Cogent Confabulation Classifier to bathing water quality assessment using remote sensing data, Ivanda, Antonia, Seric, Ljiljana, Braovic, Maja, Stipanicev, Darko, 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO), ISBN 978-953-233-103-5, 2022.
Digital Object Identifier: 10.23919/MIPRO55190.2022.9803546
[CrossRef]

[6] A Large Scale Dataset For Fire Detection and Segmentation in Indoor Spaces, Maric, Petar, Arlovic, Matej, Balen, Josip, Vdovjak, Kresimir, Damjanovic, Davor, 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), ISBN 978-1-6654-7095-7, 2022.
Digital Object Identifier: 10.1109/ICECCME55909.2022.9987926
[CrossRef]

Updated 2 days, 20 hours ago

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Faculty of Electrical Engineering and Computer Science
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